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Ravu, Venkata Sathya Sita J. S. "Compaction Strategies in Apache Cassandra : Analysis of Default Cassandra stress model." Thesis, Blekinge Tekniska Högskola, Institutionen för kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-12850.
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Context. The present trend in a large variety of applications are ranging from the web and social networking to telecommunications, is to gather and process very large and fast growing amounts of information leading to a common set of problems known collectively as “Big Data”. The ability to process large scale data analytics over large number of data sets in the last decade proved to be a competitive advantage in a wide range of industries like retail, telecom and defense etc. In response to this trend, the research community and the IT industry have proposed a number of platforms to facilitate large scale data analytics. Such platforms include a new class of databases, often refer to as NoSQL data stores. Apache Cassandra is a type of NoSQL data store. This research is focused on analyzing the performance of different compaction strategies in different use cases for default Cassandra stress model. Objectives. The performance of compaction strategies are observed in various scenarios on the basis of three use cases, Write heavy- 90/10, Read heavy- 10/90 and Balanced- 50/50. For a default Cassandra stress model, so as to finally provide the necessary events and specifications that suggest when to switch from one compaction strategy to another. Methods. Cassandra single node network is deployed on a web server and its behavior of read and write performance with different compaction strategies is studied with read heavy, write heavy and balanced workloads. Its performance metrics are collected and analyzed. Results. Performance metrics of different compaction strategies are evaluated and analyzed. Conclusions. With a detailed analysis and logical comparison, we finally conclude that Level Tiered Compaction Strategy performs better for a read heavy (10/90) workload while using default Cassandra stress model , as compared to size tiered compaction and date tiered compaction strategies. And for Balanced Date tiered compaction strategy performs better than size tiered compaction strategy and date tiered compaction strategy.
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Klapač, Milan. "Výhody a nevýhody relačních a nerelačních (noSQL) databází pro analytické úlohy." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-193931.
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This work focuses on NoSQL databases, their use for analytical tasks and on comparison of NoSQL databases with relational and OLAP databases. The aim is to analyse the benefits of NoSQL databases and their use for analytical purposes. The first part presents the basic principles of Business Intelligence, Data Warehousing, and Big Data. The second part deals with the key features of relational and NoSQL databases. The last part of the thesis describes the properties of four basic types of NoSQL databases, analyses their advantages, disadvantages and areas of application. The end of this part in-cludes specific examples of the use of NoSQL databases, together with the reasons for the selection of those solutions.
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Moatassem, Nawal N. "A Study of Migrating Biological Data from Relational Databases to NoSQL Databases." Youngstown State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1442486094.
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Günzl, Richard. "Aplikace grafové databáze na analytické úlohy." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193342.
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This diploma thesis is about graph databases, which belong to the category of database systems known as NoSQL databases, but graph databases are beyond NoSQL databases. Graph databases are useful in many cases thanks to native storing of interconnections between data, which brings advantageous properties in comparison with traditional relational database system, especially in querying. The main goal of the thesis is: to describe principles, properties and advantages of graph database; to design own convenient graph database use case and to realize the template verifying designed use case. The theoretical part focuses on the description of properties and principles of the graph database which are then compared with relational database approach. Next part dedicates analysis and explanation of the most typical use cases of the graph database including the unsuitable use cases. The last part of thesis contains analysis of own graph database use case in which several principles are defined. The principles can be applied separately. There are crucial analytical operations in the use case. The analytical operations search the causes with their rate of influence on amount or change in the value of the indicator. This part also includes the realization of the template verifying the use case in the graph database. The template consists of the database structure design, the concrete database data and analytical operations. In the end the returned results from graph database are verified by the alternative calculations without using the graph database.
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Ekberg, Albin, and Jacob Holm. "Effektiv och underhållssäker lagring av medicinsk data." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-107331.
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Creating a database to manage medical data is not the easiest. We create a database to be used for a presentation tool that presents medical data about patients that is stored in the database. We examine which of the three databases, MySQL with relational design, MySQL with EAV design and MongoDB that are best suited for storing medical data. The analysis i performed in two steps. The first step handles the database that is most effective to retriev data. The second step examines how easy it is to change the structure of the various databases. The results show that depending on whether efficiency or maintenance is most important, different databases are the best choise. MySQL with relational design proves to be most effective while MongoDB is the easiest to maintain.
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Björklund, Anna. "NoSQL Database for Software Project Data." Thesis, Umeå universitet, Institutionen för datavetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-43838.
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The field of databases have exploded in the last couple of years. New architectures try to meet the need to store more and more data and new kinds of data. The old relational model is no longer the only way and the NoSQL movement is not a trend but a new way of making the database fit the data, not the other way around.This master thesis report aims to find an efficient and well designed solution for storing and retrieving huge amounts of software project data at Tieto. It starts by looking at different architectures and trying three to see if any of them can solve the problem. The three databases selected are the relational database PostgreSQL, the graph database Neo4j and the key value store Berkeley DB. These are all implemented as a Web service and time is measured to find out which, if any, can handle the data at Tieto. In the end it is clear that the best database for Tieto is Berkeley DB. Even if Neo4j is almost as fast, it is still new and not as mature as Berkeley DB.
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Persson, Ragnvald. "NoSQL-databaser i socialt nätverk." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20692.
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Syftet med studien är att göra en fördjupning inom NoSQL-databaser och undersöka vilka uppgifter som de olika NoSQL-grupperna passar bäst till i ett socialt nätverk, som t.ex. Facebook och Twitter. Det finns fyra olika typer av NoSQL-databaser: kolumndatabaser, grafdatabaser, nyckelvärdedatabaser och dokumentdatabaser. Frågan är vilken NoSQL-databas ska man välja till en viss uppgift i ett givet socialt nätverk. När man ska utveckla ett socialt nätverk, som kräver lagring av data, är det viktigt att känna till vilken typ av databas som bör användas till en vis typ av uppgift. För att få svar på frågorna har det gjorts en undersökning över vad tidigare forskning har kommit fram till. Det har även gjorts en praktisk studie med alla fyra NoSQL-grupper i ett experiment med lagring av användaruppgifter, meddelanden och vänner.The purpose of the study is to deepen within NoSQL databases and investigate what tasks the different NoSQL groups fit best in a social network, such as Facebook and Twitter. The data is, for example, about the storage of personal data or social networking. There are four different types of NoSQL databases: column databases, graph databases, key value databases and document databases. The question is which NoSQL database should be chosen for a particular task in a given social network. When developing a social network that requires data storage, it is important to know what kind of database should be used for a certain type of task.In order to answer the questions, an investigation has been made of what previous research has reached. There has also been a practical study of all four NoSQL groups in an experiment with storing user information, messages and friends.
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Mendoza, Jayo Rubén G., Carlos Raymundo, Francisco Domínguez Mateos, and Rodríguez José María Alvarez. "Convergence model for the migration of a relational database to a NoSQL database." International Institute of Informatics and Systemics, IIIS, 2017. http://hdl.handle.net/10757/656362.
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Pretorius, Dawid Johannes. "NoSQL database considerations and implications for businesses." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85727.
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Thesis (MComm)--Stellenbosch University, 2013.ENGLISH ABSTRACT: NoSQL databases, a new way of storing and retrieving data, can provide businesses with many benefits, although they also pose many risks for businesses. The lack of knowledge among decision-makers of businesses regarding NoSQL databases can lead to risks left unaddressed and missed opportunities. This study, by means of an extensive literature review, identifies the key drivers, characteristics and benefits of a NoSQL database, thereby providing a clear understanding of the subject. The business imperatives related to NoSQL databases are also identified and discussed. This can help businesses to determine whether a NoSQL database might be a viable solution, and to align business and information technology (IT) objectives. The key strategic and operational IT risks are also identified and discussed, based on the literature review. This can help business to ensure that the risks related to the use of NoSQL databases are appropriately addressed. Lastly, the identified risks were mapped to the processes of COBIT (Control Objectives for Information and Related Technology) to inform a business of the highest risk areas and the associated focus areas.
AFRIKAANSE OPSOMMING: NoSQL databasisse, 'n nuwe manier om data te stoor en herwin, het die potensiaal om baie voordele vir besighede in te hou, maar kan ook baie risiko's teweeg bring. Gebrekkige kennis onder besigheidsbesluitnemers oor NoSQL databasisse kan lei tot onaangespreekte risiko’s en verlore geleenthede. Hierdie studie, deur middel van 'n uitgebreide literatuuroorsig, identifiseer die sleutel eienskappe, kenmerke en voordele van 'n NoSQL databasis, om sodoende 'n duidelike begrip van die onderwerp te verkry. Die besigheidsimperatiewe wat verband hou met NoSQL databasisse is ook geïdentifiseer en bespreek. Dit kan besighede help om te bepaal of 'n NoSQL databasis 'n werkbare oplossing kan wees, asook sake- en inligtingstegnologie (IT) doelwitte in lyn met mekaar bring. Na aanleiding van die literatuurstudie is die sleutel-strategiese en operasionele IT-risiko's geïdentifiseer en bespreek. Dit kan help om aan besighede sekerheid te verskaf dat die risiko's wat verband hou met die gebruik van NoSQL databasisse toepaslik aangespreek word. Laastens is die geïdentifiseerde risiko's gekoppel aan die prosesse van COBIT om 'n besigheid van die hoë-risiko areas en die gepaardgaande fokusareas in te lig.
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Vizina, Petr. "NoSQL databáze pro data senzorů s podporou časových řad." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363797.
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This thesis deals with NoSQL databases, which can be used for effective storage of sensors data with character of time series. The aim is to design and implement own solution for database designed to store time series data, with usage of NoSQL.
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Yin, Suna. "Creating NoSQL Database Functionality on the SensibleThings Platform." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-25504.
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Nygaard, Knut, and Eivind Siqveland Larsen. "Automatic scaling and maintenance of a NoSQL database." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-26758.
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NoSQL databases often support scalability and high availability. We address Voldemort, which is a popular, highly available NoSQL database that can be run on several nodes. Voldemort can be cumbersome to setup and maintain. As clusters grow in size, scaling into hundreds of nodes, management and administrative tasks become increasingly complex. We have therefore focused on automating management of a running cluster of nodes.We have migrated the configuration storage of the Voldemort database from local XML files on disk to global objects using Apache ZooKeeper.Using native tools and ZooKeeper coordination, we have implemented a fault tolerant, redundant management service. The service manages node discovery, configuration generation and propagation. It also has components for live monitoring and adjustment of responsibility to match each nodes available system resources.
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Vrbík, Tomáš. "Srovnání distribuovaných "NoSQL" databází s důrazem na výkon a škálovatelnost." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-124673.
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This paper focuses on NoSQL database systems. These systems currently serve rather as supplement than replacement of relational database systems. The aim of this paper is to compare 4 selected NoSQL database systems (MongoDB, Apache Cassandra, Apache HBase and Redis) with a main focus on performance and scalability. Performance comparison is done using simulated workload in a 4 nodes cluster environment. One relational SQL database is also benchmarked to provide comparison between classic and modern way of maintaining structured data. As the result of comparison I found out that none of these database systems can be labeled as "the best" as each of the compared systems is suitable for different production deployment.
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Landbris, Johan. "A Non-functional evaluation of NoSQL Database Management Systems." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-46804.
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NoSQL is basically a family name for all Database Management Systems (DBMS) that is not Relational DBMS. The fast growth of all social networks has led to a huge amount of unstructured data that NoSQL DBMS is supposed to handle better than Relational DBMS. Most comparisons performed are between Relational DBMS and NoSQL DBMS. In this paper, the comparison is about non-functional properties for different types of NoSQL DBMS instead. Three of the most common NoSQL types are Document Stores, Key-Value Stores and Column Stores. The most used DBMS of those types are MongoDB, Redis and Apache Cassandra. After working with the databases and performing YCSB Benchmarking the conclusion is that if the database should handle an enormous amount of data, Cassandra is most probably best choice. If speed is the most important property and if all data fits within the memory; Redis is probably the most well suited database. If the database needs to be flexible and versatile, MongoDB is probably the best choice.
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Pecsérke, Róbert. "Podpora MongoDB pro UnifiedPush Server." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255415.
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Tato diplomová práce se zabývá návrhem a implementací rozšíření pro UnifiedPush Server, které serveru umožní přistupovat k nerelační databázi MongoDB a využívá potenciál horiznotální škálovatelnosti neralačních databází. Součástí práce je i návrh výkonnostních testů a porovnání výkonu při behu na jednom a vícero uzlích, návrh migračního scénáře z MySQL na MongoDB, identifikace úzkých míst. Aplikace je implementována v jazyce Java a využívá Java Persistence API pro přístup k databázím. Pro přístup k nerelačním databázím používá implementaci standardu JPA Hibernate OGM.
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Petera, Martin. "Srovnání distribuovaných "No-SQL" databází s důrazem na výkon a škálovatelnost." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193233.
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This thesis deals with NoSQL database performance issue. The aim of the paper is to compare most common prototypes of distributed database systems with emphasis on performance and scalability. Yahoo! Cloud Serving Benchmark (YCSB) is used to accomplish the aforementioned aim. The YCSB tool allows performance testing through performance indicators like throughput or response time. It is followed by a thorough explanation of how to work with this tool, which gives readers an opportunity to test performance or do a performance comparison of other distributed database systems than of those described in this thesis. It also helps readers to be able to create testing environment and apply the testing method which has been listed in this thesis should they need it. This paper can be used as a help when making an arduous choice for a specific system from a wide variety of NoSQL database systems for intended solution.
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Chavez, Alcarraz Erick, and Manuel Moraga. "Linked data performance in different databases : Comparison between SQL and NoSQL databases." Thesis, KTH, Data- och elektroteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-146602.
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Meepo AB was investigating the possibility of developing a social rating and recommendation service. In a recommendation service, the user ratings are collected in a database, this data is then used in recommendation algorithms to create individual user recommendations. The purpose of this study was to find out which demands are put on a DBMS, database management system, powering a recommendation service, what impact the NoSQL databases have on the performance of recommendation services compared to traditional relational databases, and which DBMS is most suited for storing the data needed to host a recommendation service. Five distinct NoSQL and Relational DBMS were examined, from these three candidates were chosen for a closer comparison. Following a study of recommendation algorithms and services, a test suite was created to compare DBMS performance in different areas using a data set of 100 million ratings. The results show that MongoDB had the best performance in most use cases, while Neo4j and MySQL struggled with queries spanning the whole data set. This paper however never compared performance for real production code. To get a better comparison, more research is needed. We recommend new performance tests for MongoDB and Neo4j using implementations of recommendation algorithms, a larger data set, and more powerful hardware.Meepo AB undersökte möjligheten att utveckla en social betygs- och rekommendationstjänst. I en rekommendationstjänst samlas användarbetyg i en databas, för att sedan användas i en rekommendationsalgoritm för att skapa individuella rekommendationer till användarna. Syftet med studien var att ta reda på vilka krav som ställs på ett DBMS, databassystem, som driver en rekommendationstjänst, vilken inverkan NoSQL-databaser har på prestandan för rekommendationstjänster jämfört med traditionella relationsdatabaser och vilket DBMS som är mest lämpat för användning i en rekommendation tjänst. Fem olika NoSQL- och Relationsdatabaser undersöktes, från dessa valdes tre kandidater ut för en närmare jämförelse. Efter en studie i rekommendationsalgoritmer och rekommendationstjänster skapades en testsvit för att jämföra databasernas prestanda i olika områden. Till detta användes ett dataset med 100 miljoner betyg. Resultaten visar att MongoDB hade bäst prestanda i flest användningsfall, medan Neo4j och MySQL hade problem med sökningar som sträcker sig över hela datasetet. I denna uppsats jämförs dock inte prestandan med riktig produktionskod. För en bättre jämförelse behövs mer forskning. Vi rekommenderar nya prestandamätningar för MongoDB och Neo4j med implementationer av rekommendationsalgoritmer, ett större dataset och mer kraftfull hårdvara.
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Hedman, Jennifer, and Mikael Holmberg. "Jämförelse av NoSQL-databas och SQL-baserad relationsdatabas : En förklarande studie för när NoSQL kan vara att föredra framför en relationsdatabas." Thesis, Högskolan Dalarna, Informatik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:du-29817.
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With the explosive development of the mobile world, web applications and Big Data, new requirements for storage capacity and speed of database systems have arisen. The traditional relational database that has long dominated the marked has received competition because of its lack in speed and scalability. NoSQL is a collective name for databases that are not based on the traditional relational model. NoSQL databases are designed to easily expand their storage capacity while delivering high performance. NoSQL databases have been around for decades but the need for them is relatively new. Our partner expressed a desire to know what differences exist between NoSQL and the traditional relational database. To clarify these differences, we have answered the following questions in this work: When can a NoSQL database be preferred to a relational database? What are the differences in database performance? In order to answer these questions, a literature study has been conducted together with experiments where we test which performance differences exist between the selected databases. Performance tests have been performed with the benchmarking tool Yahoo Cloud Serving Benchmark, to verify or falsify the enhanced performance of the NoSQL databases. The hypotheses were falsified in both NoSQL databases. The results showed that the relational database performed better than the cloud based NoSQL databases, but also that the relational database performance deteriorates when the load increased. The results of the experiments are combined with the literature study and together answer our questions. The conclusion is that no database performs better than another one, it is the requirements of the data to be stored. From these requirements, analyses can be made to draw conclusions about what kind of database is preferable.
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Ait, Ouassarah Azhar. "ADI : A NoSQL system for bi-temporal databases." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI046/document.
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La complexité et la dynamique de l'environnement dans lequel évolue chaque entreprise requiert de la part de ses managers la capacité de prendre des décisions pertinentes dans un laps de temps très court afin de s'accroître. Pour cela, l'analyse des données générées par l'activité de l'entreprise peut être une précieuse source d'information. L'Intelligence Opérationnelle (IO) est une classe de systèmes d'aide à la décision permettant aux managers d'avoir une très bonne compréhension de la situation de l'entreprise, à travers l'analyse de l'activité passée et présente. Dans ce contexte, les notions de temps et de traçabilité sont primordiales dans la compréhension de l'évolution de l'activité de l'entreprise à travers le temps. Dans cette thèse, nous présentons Axway Decision Insight (ADI), une solution d'IO développée par Axway. Son composant clé est un SGBD orienté-colonnes et bi-temporel développé en interne par l'entreprise pour répondre aux besoins spécifiques de l'IO. Ses capacités bi-temporelles lui permettent de gérer nativement aussi bien l'évolution des données dans la réalité modélisée (temps de validité) que l'évolution des données dans la base de données (temps de transaction). Nous commencerons par présenter la solution ADI en nous focalisant sur deux éléments importants: 1) l'interface graphique qui permet la conception et l'utilisation d'ADI sans écrire la moindre ligne de code. 2) L'approche adoptée pour modéliser les données bi-temporelles. Ensuite, nous présenterons un benchmark bi-temporel destiné ADI.Après cela, nous présenterons deux optimisations pour ADI. La première permet de pré-calculer et matérialiser les opérations d'agrégation, ce qui permet de réduire le temps nécessaire à la mise à jour de interface graphique d'ADI. La deuxième optimisation ordonne l'exécution des opérateurs de jointure des plans de requêtes en utilisant un modèle coût basé sur des statistiques sur des données bi-temporelles. Pour ces optimisations, nous avons effectué des expérimentations en utilisant notre benchmark, et qui ont démontré leurs intérêtsNowadays, every company is operating in very dynamic and complex environments which require from its managers to have a deep understanding of its business in order to take rapid and relevant decisions, and thus maintain or improve their company's activities. They can rely on analyzing the data deluge generated by the company's activities. A new class of systems has emerged in the decision support system galaxy called "Operational Intelligence" (OI) to meet this challenge. The objective is to enable operational managers to understand what happened in the past as well as what is currently happening in their business. In this context, the notions of time and traceability turns out to play a crucial role to understand what happened in the company and what is currently happening in the company. In this thesis, we present "Axway Decision Insight" (ADI), an "Operational Intelligence" solution developed by Axway. ADI's key component is a proprietary bi-temporal and column-oriented DBMS that has specially been designed to meet OI requirements. Its bi-temporal capabilities enable to catch both data evolution in the modeled reality (valid time) and in the database (transaction time).We first introduce ADI by focusing on two topics: 1) the GUI that makes the platform "code-free". 2) The adopted bi-temporal modeling approaches. Then we propose a performance benchmark that meets ADI's requirements. Next, we present two bi-temporal query optimizations for ADI. The first one consists in redefining a complex bi-temporal query into: 1) a set of continuous queries in charge of computing aggregation operations as data is collected. 2) A bi-temporal query that accesses the continuous queries' results and feeds the GUI. The second one is a cost-based optimization that uses statistics on bi-temporal data to determine an "optimal" query plan. For these two optimizations, we conducted some experiments, using our benchmark, which show their interests
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Ogunyadeka, Adewole C. "Transactions and data management in NoSQL cloud databases." Thesis, Oxford Brookes University, 2016. https://radar.brookes.ac.uk/radar/items/c87fa049-f8c7-4b9e-a27c-3c106fcda018/1/.
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NoSQL databases have become the preferred option for storing and processing data in cloud computing as they are capable of providing high data availability, scalability and efficiency. But in order to achieve these attributes, NoSQL databases make certain trade-offs. First, NoSQL databases cannot guarantee strong consistency of data. They only guarantee a weaker consistency which is based on eventual consistency model. Second, NoSQL databases adopt a simple data model which makes it easy for data to be scaled across multiple nodes. Third, NoSQL databases do not support table joins and referential integrity which by implication, means they cannot implement complex queries. The combination of these factors implies that NoSQL databases cannot support transactions. Motivated by these crucial issues this thesis investigates into the transactions and data management in NoSQL databases. It presents a novel approach that implements transactional support for NoSQL databases in order to ensure stronger data consistency and provide appropriate level of performance. The novelty lies in the design of a Multi-Key transaction model that guarantees the standard properties of transactions in order to ensure stronger consistency and integrity of data. The model is implemented in a novel loosely-coupled architecture that separates the implementation of transactional logic from the underlying data thus ensuring transparency and abstraction in cloud and NoSQL databases. The proposed approach is validated through the development of a prototype system using real MongoDB system. An extended version of the standard Yahoo! Cloud Services Benchmark (YCSB) has been used in order to test and evaluate the proposed approach. Various experiments have been conducted and sets of results have been generated. The results show that the proposed approach meets the research objectives. It maintains stronger consistency of cloud data as well as appropriate level of reliability and performance.
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Höggren, Lindahl Patrik, and Klas Tärnström. "Utvecklares upplevda problematik vid användande av NoSQL-databaser." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-56967.
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Salvatori, Riccardo. "Analisi delle strategie di modellazione dei dati su database NoSQL." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23172/.
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Negli ultimi anni, i sistemi NoSQL si sono rivelati una soluzione efficace alle stringenti esigenze del web e dei sistemi di big data, grazie alle caratteristiche di scalabilità e flessibilità che superano le limitazioni imposte dai classici RDBMS.
La crescente popolarità è accompagnata però dalla mancanza di metodologie generali ed efficaci per la modellazione di dati, che permettano di sfruttare al meglio le possibilità offerte dal mondo non relazionale. Infatti, a differenza dei database relazionali, per cui esiste una vasta letteratura sul tema, molte tecniche di progettazione in ambito NoSQL sono proposte sotto forma di linee guida e best practice, per lo più dettate dall'esperienza, che spesso vanno adattate al carico di lavoro e alla specifica implementazione.
In questa tesi sono state analizzate le diverse strategie di modellazione in ambito NoSQL, evidenziando il ruolo fondamentale che hanno nel determinare le prestazioni finali del database.
L'analisi è stata effettuata utilizzando il benchmark TPC-C, su due popolari database NoSQL: MongoDB e Cassandra.
Inoltre, è stato progettato un indicatore che permette di avere un'approssimazione a priori delle prestazioni di una de-normalizzazione. L'indicatore si è dimostrato efficace per i database MongoDB e Cassandra nell'individuare le modellazioni dei dati ottimali per il carico di lavoro previsto.
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Monjaras, Alvaro, Enrique Bcndezu, and Carlos Raymundo. "Decision Tree Model to Support the Successful Selection of a Database Engine for Novice Database Administrators." Institute of Electrical and Electronics Engineers Inc, 2019. http://hdl.handle.net/10757/656346.
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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.There are currently several types of databases that have different ways of manipulating data that affects the performance of transactions when dealing with the information stored. And it is very important for companies to manage information fast, so they do not lose any operation because of a bad performance of a database, in the same way, they need to operate fast while keeping the integrity of the information. Likewise, every database category's purpose is to serve a specific or specifics use cases to perform fast to manage the information when needed, so in this paper, we study and analyze the SQL, NoSQL and In Memory databases to understand their fit uses cases and make performance tests to build a decision tree that can help to take the decision to choose what database category to use to maintain a good performance. The precision of the tests of relational databases was 96.26% in NoSQL databases was 91.83% and finally in IMDBS was 93.87%.
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Pulgatti, Leandro Duarte. "Data migration between different data models of NOSQL databases." reponame:Repositório Institucional da UFPR, 2017. http://hdl.handle.net/1884/49087.
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Orientador : Marcos Didonet Del FabroDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 17/02/2017
Inclui referências : f. 76-79
Resumo: Desde sua origem, as bases de dados Nosql têm alcançado um uso generalizado. Devido à falta de padrões de desenvolvimento nesta nova tecnologia emergem grandes desafios. Existem modelos de dados , linguagens de acesso e frameworks heterogêneos, o que torna a migração de dados ainda mais complexa. A maior parte das soluções disponíveis hoje se concentra em fornecer uma representação abstrata e genérica para todos os modelos de dados. Essas soluções se concentram em adaptadores para acessar homogeneamente os dados, mas não para implementar especificamente transformações entre eles. Essas abordagens muitas vezes precisam de um framework para acessar os dados, o que pode impedir de usá-los em alguns cenários. Entre estes desafios, a migração de dados entre as várias soluções revelou-se particularmente difícil. Esta dissertação propõe a criação de um metamodelo e uma série de regras capazes de auxiliar na tarefa de migração de dados. Os dados podem ser convertidos para vários formatos desejados através de um estado intermediário. Para validar a solução foram realizados vários testes com diversos sistemas e utilizando dados reais disponíveis. Palavras Chave: NoSql Databases. Metamodelo. Migração de Dados.
Abstract: Since its origin the NoSql Database have achieved widespread use. Due to the lack of standards for development in this new technology great challenges emerges. Among these challenges, the data migration between the various solutions has proved particularly difficult. There are heterogeneous datamodels, access languages and frameworks available, which makes data migration even more complex. Most part of the solutions available today focus on providing an abstract and generic representation for all data models. These solutions focus in design adapters to homogeneously access the data, but not to specifically implement transformations between them. These approaches often need a framework to access the data, which may prevent from using them in some scenarios. This dissertation proposes the creation of a metamodel and a series of rules capable of assisting in the data migration task. The data can be converted to various desired formats through an intermediate state. To validate the solution several tests were performed with different systems and using real data available. Key-words: NoSql Databases. Metamodel. Data Migration.
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Sortelius, Erik, and Gabriellle Önnestam. "Påverkan av query-komplexitet på söktiden hos NoSQL-databaser." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15970.
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Arbetet jämför fyra olika NoSQL-databaser med fokus på tidseffektivitet. De fyra databaserna är MongoDB, RavenDB, ArangoDB och Couchbase. Studien består av en benchmark för att mäta tidseffektiviteten av de fyra databaserna och en litteraturstudie av hur tidseffektiviteten påverkas av optimeringslösningar. Tillsammans bidrar dessa metoder till en slutsats från båda perspektiven då de kompletterar varandra och ger en grund för resultatets betydelse. Arbetets grund ligger i ett tidigare examensarbete som går ut på att jämföra en SQL-databas mot en NoSQL-databas med en benchmark. Resultatet av studien visar att för de flesta databaser så ökar söktiden för en query i korrelation med ökningen av query-komplexiteten, och att tidseffektiviteten mellan de olika databaserna varierar vid sökningar med hög komplexitet. Framtida arbeten som kan baseras på denna studie är att göra en liknande benchmark på ett dataset som är större eller att en annan typ av databas används.
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Muhammad, Yousaf. "Evaluation and Implementation of Distributed NoSQL Database for MMO Gaming Environment." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-159864.
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Kharboutli, Zacky. "NoSQL Database Selection Focused on Performance Criteria for Web-driven Applications." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-88608.
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This paper delivers a comparative analysis of the performance of three of the NoSQL technologies in Web applications. These technologies are graph stores, key-value stores, and document stores. The study aims to assist developers and organizationsin picking the suitable NoSQL solution for their application. For this purpose, three identical e-book applications were developed. Each of these is connected to adatabase from the selected technologies to examine how they perform compared toeach other against various performance measures.
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Heller, Stanislav. "MongoDB jako datové úložiště pro Google App Engine SDK." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-235455.
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In this thesis, there are discussed use-cases of NoSQL database MongoDB implemented as a datastore for user data, which is stored by Datastore stubs in Google App Engine SDK. Existing stubs are not very well optimized for higher load; they significantly slow down application development and testing if there is a need to store larger data sets in these storages. The analysis is focused on features of MongoDB, Google App Engine NoSQL Datastore and interfaces for data manipulation in SDK - Datastore Service Stub API. As a result, there was designed and implemented new datastore stub, which is supposed to solve problems of existing stubs. New stub uses MongoDB as a database layer for storing testing data and it is fully integrated into Google App Engine SDK.
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Walldén, Marcus, and Aylin Özkan. "A graph database management system for a logistics-related service." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205184.
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Higher demands on database systems have lead to an increased popularity of certain database system types in some niche areas. One such niche area is graph networks, such as social networks or logistics networks. An analysis made on such networks often focus on complex relational patterns that sometimes can not be solved efficiently by traditional relational databases, which has lead to the infusion of some specialized non-relational database systems. Some of the database systems that have seen a surge in popularity in this area are graph database systems. This thesis presents a prototype of a logistics network-related service using a graph database management system called Neo4j, which currently is the most popular graph database management system in use. The logistics network covered by the service is based on existing data from PostNord, Sweden’s biggest provider of logistics solutions, and primarily focuses on customer support and business to business. By creating a prototype of the service this thesis strives to indicate some of the positive and negative aspects of a graph database system, as well as give an indication of how a service using a graph database system could be created. The results indicate that Neo4j is very intuitive and easy to use, which would make it optimal for prototyping and smaller systems, but due to the used evaluation method more research in this area would need to be carried out in order to confirm these conclusions.Högre krav på databassystem har lett till en ökad popularitet för vissa databassystemstyper i några nischområden. Ett sådant nischområde är grafnätverk, såsomsociala nätverk eller logistiknätverk. Analyser på grafnätverk fokuserar ofta påkomplexa relationsmönster som ibland inte kan lösas effektivt av traditionella relationsdatabassystem, vilket har lett till att vissa specialiserade icke-relationella databassystem har blivit populära alternativ. Många av de populära databassystemen inom detta område är grafdatabassystem. Detta arbete presenterar en prototyp av en logistiknätverksrelaterad tjänst som använder sig av ett grafdatabashanteringssystem som heter Neo4j, vilket är det mest använda grafdatabashanteringssystemet. Logistiknätverket som täcks av tjänsten är baserad på existerande data från PostNord, Sveriges ledande leverantör av logistiklösningar, och fokuserar primärt på kundsupport och företagsrelaterad analys. Genom att skapa en prototyp av tjänsten strävar detta arbete efter att uppvisa vissa av de positiva och negativa aspekterna av ett grafdatabashanteringssystem samt att visa hur en tjänst kan skapas genom att använda ett grafdatabashanteringssystem. Resultaten indikerar att Neo4j är väldigt intuitivt och lättanvänt, vilket skulle göra den optimal för prototyping och mindre system, men på grund av den använda evalueringsmetoden så behöver mer forskning inom detta område utföras innan dessa slutsatser kan bekräftas.
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Miiro, Fabian, and Mikael Nääs. "SQL and NoSQL databases : A CASE STUDY IN THE AZURE CLOUD." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186398.
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I denna rapport jämförs Azure SQL Database med NoSQL lösningen DocumentDB, under förutsättningarna givna av ett turbaserat flerspelarspel. NoSQL är en relativt ny typ av databas, som till skillnad från dess relationsbaserade kusin har nya lovord angående fantastisk prestanda och oändlig skalbarhet. Det sägs att det är skapt för dagens problem utan gårdagens begränsningar. Warmkitten vill ta reda på om löftena kring NoSQL håller i deras scenario. Eller om den nuvarande SQL lösningen är en bättre match för deras spel med tanke på skalning, snabbhet och anvädningen utav .NET. Jämförelsen gjordes genom att först skapa ett testramverk för spelets flerspelar funktioner. Sedan optimerades både den relations- och den icke-relationsbaserade lösningen, baserat på rekommendationer och experters utlåtande. Testerna kördes sedan under förhållanden som skulle återspegla verkligheten. Rapporten visar att denna nya typ utav databaser helt klart är mogna nog att i vissa scenarion användas istället för de relationsbaserade databaserna, givet att tillräckligt mycket tid ges åt att förstå skillnaderna mellan databastyperna och vad det innebär. Extra betänketid bör läggas på hur NoSQL skalar samt vilka skillnader som det innebär när relations-begränsningarna försvinner. Prestandamässigt så är DocumentDB snabbare under normal användning när det finns lugnare stunder, SQL är bättre för applikationer som behöver köra under långa stunder med hög användning utav databasen. Rapportens slutsats blir en rekommendation till Warmkitten att fortsätta med den redan utvecklade SQL lösningen. Detta då prestandaförbättringarna från NoSQL inte väger upp för den ökade transaktionskomplexiteten, då spelet använder transaktioner i hög utsträckning.This paper was created to compare Azure SQL Database to the Azure NoSQL solution DocumentDB. This case study is done in the scope of a turn-based multiplayer game created by Warmkitten. NoSQL is a new type of databases, instead of the relational kind we are used to, this new type gives promises of increased performance and unlimited scalability. It is marketed that it is created for the problems of today and not bound by yesterday’s limitations. Warmkitten would like to gain insight if the promises from NoSQL holds for the game they are developing or if the current SQL solution fit their needs. They are most interested in the areas of scaling, performance and .NET interoperability. The comparison was carried out by creating a test suite testing the game functionalities. Then both the SQL and NoSQL solution was optimized based on best practices and expert guidelines. The tests were then run under circumstances mimicking real-world scenarios. The paper shows that NoSQL is a valid replacement to SQL, if enough time and thought is put into the implementation. Given that NoSQL is a good fit for the problem at hand. Our paper shows that performance wise NoSQL is faster under normal load when there are times with less load, SQL is better for applications that will have continuously heavy load. The final verdict of this paper is a recommendation for Warmkitten to continue using SQL for their game. This is because the recorded performance improvements does not outweighs the transactional problems seen in this case study created by the transactional nature of the game.
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Ishak, Marwah. "Prevention of Privilege Abuse on NoSQL Databases : Analysis on MongoDB access control." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296525.
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Database security is vital to retain confidentiality and integrity of data as well as prevent security threats such as privilege abuse. The most common form of privilege abuse is excessive privilege abuse, which entails assigning users with excessive privileges beyond their job function, which can be abused deliberately or inadvertently. The thesis’s objective is to determine how to prevent privilege abuse in the NoSQL database MongoDB. Prior studies have noted the importance of access control to secure databases from privilege abuse. Access control is essential to manage and protect the accessibility of the data stored and restrict unauthorised access. Therefore, the study analyses MongoDB’s embedded access control through experimental testing to test various built-in and advanced privileges roles in preventing privilege abuse. The results indicate that privilege abuse can be prevented if users are granted roles composed of the least privileges. Additionally, the results indicate that assigning users with excessive privileges exposes the system to privilege abuse. The study also underlines that an inaccurate allocation of privileges or permissions to users of databases may have profound consequences for the system and organisation, such as data breach and data manipulation. Hence, organisations that utilise information technology should be obliged to protect their interests and databases from others and their members through access control policies.Datasäkerhet är avgörande för att bevara datats konfidentialitet och integritet samt för att förhindra säkerhetshot som missbruk av privilegier. Missbruk av överflödig privilegier, är den vanligaste formen av privilegier missbruk. Detta innebär att en användare tilldelas obegränsad behörighet utöver det som behövs för deras arbete, vilket kan missbrukas medvetet eller av misstag. Examensarbetets mål är att avgöra hur man kan förhindra missbruk av privilegier i NoSQL-databasen MongoDB. Tidigare studier har noterat vikten av åtkomstkontroll för att säkra databaser från missbruk av privilegier. Åtkomstkontroll är viktigt för att hantera och skydda åtkomlighet för de lagrade data samt begränsa obegränsad åtkomst. Därför analyserar arbetet MongoDBs inbäddade åtkomstkontroll genom experimentell testning för att testa olika inbyggda och avancerade priviligierade roller för att förhindra missbruk av privilegier. Resultaten indikerar att missbruk av privilegier kan förhindras om användare får roller som har färre privilegier. Dessutom visar resultaten att tilldelning av användare med obegränsade privilegier utsätter systemet för missbruk av privilegier. Studien understryker också att en felaktig tilldelning av privilegier eller behörigheter för databasanvändare kan få allvarliga konsekvenser för systemet och organisationen, såsom dataintrång och datamanipulation. Därför bör organisationer som använder informationsteknologi ha som plikt att skydda sina tillgångar och databaser från obehöriga men även företagets medarbetare som inte är beroende av datat genom policys för åtkomstkontroll.
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Jansson, Jens, Alexandar Vukosavljevic, and Ismet Catovic. "Performance comparison between multi-model, key-value and documental NoSQL database management systems." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19857.
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This study conducted an experiment that compares the multi-model NoSQL DBMS ArangoDB with other NoSQL DBMS, in terms of the average response time of queries. The DBMS compared in this experiment are the following: Redis, MongoDB, Couchbase, and OrientDB. The hypothesis that is answered in this study is the following: “There is a significant difference between ArangoDB, OrientDB, Couchbase, Redis, MongoDB in terms of the average response time of queries”. This is examined by comparing the average response time of 1 000, 100 000, and 1 000 000 queries between these database systems. The results show that ArangoDB performs worse compared to the other DBMS. Examples of future work include using additional DBMS in the same experiment and replacing ArangoDB with another multi-model DBMS to decide whether such a DBMS, in general, performs worse than single-model DBMS.
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Espling, Sebastian. "Faktorer att beakta vid val av databasmodell för en molntjänst : Ur ett mikroföretags perspektiv." Thesis, Högskolan i Skövde, Institutionen för kommunikation och information, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-6025.
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En databasmodell är en viktig del av en applikation och för företag som utvecklar molntjänster är det viktigt att databasmodellen kan hantera föränderlig och växande data. För mikroföretag som utvecklar molntjänster är val av databasmodell en stor investering. Ett medvetet val måste göras för att säkerställa att rätt databasmodell väljs utefter de förutsättningar, resurser och syfte man har med sin applikation. Då mikroföretag inte har samma resurser i form av kapital, kunskap och kompetens som större företag är detta val än mer viktigt. I denna uppsats har en kvalitativ undersökning genomförts i syfte att svara på två delfrågor och en huvudfråga. Delfrågorna skall ligga som grund till att svara på huvudfrågan i uppsatsen. Huvudfrågan ämnar identifiera vilka faktorer mikroföretag som utvecklar molntjänster bör beakta vid val avdatabasmodell för deras förutsättningar och syfte. Delfråga 1 ämnar identifiera vilka fördelar samt nackdelar som finns med databasmodellerna relationsdatabaser och NoSQL databaser. Delfråga 2 ämnar klargöra om det finns några faktorer som påverkar valet av databasmodell speciellt för en molntjänst. Resultatet av uppsatsen och den slutsats som arbetet resulterade i var att mikroföretag med hjälp av de för- och nackdelar som identifierats kan utvärdera vilken databasmodell som passar deras förutsättningar och syfte. Då syfte och förutsättningar skiljer sig mellan företag är detta en analys som de själva måste genomföra. Studien visade att finns vissa speciella aspekter att beakta för valet av databasmodell för en molntjänst men att det inte skiljer sig avsevärt från vilka aspekter som beaktas för val av databasmodeller i allmänhet.
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Skarman, Mattias, and Jacob Östelid. "Relationsdatabas eller NoSQL? : En jämförelse mellan MSSQL och MongoDB." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43255.
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Midroc automation uses databases for many different projects, both internally and in customer projects. At present, they are mainly using relational databases. There is an interest in researching different types of databases not based on the relational model. Midroc automation wants to know if there are any advantages of using a non-relational database. This project will compare two different databases. To make this comparison Microsoft SQL and MongoDB has been selected. MongoDB is a document type database which belongs to the category of non-relational databases commonly referred to as NoSQL. An application with a GUI and CRUD operations for each database has been implemented. This implementation was done using C# .NET in Visual Studio. The result of the comparison shows that MongoDB is more flexible while developing a database. It is also easier to make changes to an existing database while working with MongoDB. It is however harder to find information and support online when working with MongoDB.Midroc Automation använder databaser till många olika projekt, både internt och mot sina kunder. Idag använder de främst databaser baserade på relationsmodellen. De är intresserade av att utreda om det finns några andra typer av databaser som inte är baserade på relationsmodellen och också om dessa skulle innebära några fördelar. I detta projekt kommer man att jämföra två olika databaser. För att göra denna jämförelse har man valt att undersöka Microsoft SQL och MongoDB. MongoDB är en databas av dokumenttyp som tillhör de moderna icke-relationella databaserna kallade NoSQL. För att göra jämförelsen har en applikation med tillhörande GUI och CRUD-operationer implementerats för varje databas. Implementationen har gjorts med hjälp av C# .NET i utvecklingsverktyget Visual Studio. Resultatet av jämförelsen visar att MongoDB är mer flexibelt vid utveckling av databasen. Det är också enklare att göra ändringar till en befintlig databas med MongoDB. Det är dock svårare att hitta information och hjälp online då man utvecklar en Mongo databas.
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Öhrn, Henrik. "NoSQL-databaser och utnyttjandet av en grafdatabas i ett transportnätverk." Thesis, University of Gävle, Department of Industrial Development, IT and Land Management, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-7016.
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Den allmänna kunskapen om NoSQL-databaser är begränsad. Den här uppsatsen koncentrerar sig på att sammanställa egenskaper och information om för- och nackdelar som rör dessa databastyper samt relationsdatabaser i en undersökning. Uppsatsen belyser även användningsområden för de olika databastyperna och i en fallstudie testas en grafdatabas förmåga att representera och utföra sökningar av data från ett järnvägsspårnät. Problemområdena undersöktes genom att samla information om olika typer av databaser från artiklar och böcker. Tillämpningsfallet i fallstudien implementerades och testades i en grafdatabas. Resultatet av undersökningen visade att NoSQL-databaser är ett intressant alternativ i vissa fall men att mycket hänsyn måste tas innan man väljer vilken typ av databas som är mest lämpad i den specifika tillämpningen. Resultatet av fallstudien visar att en grafdatabas är särdeles lämpad för att representera och utföra operationer på ett transportnätverk. Detta till stora delar beroende på dess förmåga att representera kopplingarna i ett transportnätverk och i form av de operationerna som finns i grafteorin och som grafmodellen erbjuder.Nyckelord: nosql, relationsdatabas, nyckel/värde-databas, kolumndatabas, objektdatabas, dokumentdatabas, grafdatabas, järnvägsnätverk, transportnätverk
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Rothsberg, Johan. "Evaluation of using NoSQL databases in an event sourcing system." Thesis, Linköpings universitet, Databas och informationsteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-123193.
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An event store is a database for storing events in an event sourcing system. Instead of storing the current state, a very common way to persist data, an event sourcing system captures all changes to an application state as a sequence of events. Usually the event store is a relational database. Relational databases have several drawbacks and therefore NoSQL databases have been developed. The purpose of this thesis is to explore the possibility of using a NoSQL database in an event sourcing system. We will see how data is stored in an event store and then evaluate di↵erent solutions to find a suitable database. The graph database Neo4j was selected to be further investigated and a Neo4j event store has been implemented. At last the implemented solution is evaluated against the existing event store that uses a relational database. The conclusion of this thesis is that event store data could easily be modeled in Neo4j but some queries became complex to implement. The performance tests showed us that the implemented event store had poorer performance than the existing one using a relational database.
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Persson, Peter, Johan Sjölin, and Thomas Dahlberg. "Databaser i molnet : En prestanda utvärdering." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-20699.
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Abstract As a developer of database-driven applications you will be faced with difficult choices, when it comes to choosing database, server and programming language. For the result to be satisfactory it requires the different techniques to interact well with each other and also fulfill performance expectations. This is even more important when the application is deployed to the cloud and the response time plays a major role.This paper evaluates different databases and their performance. To test the databases there was an application made in the server script language PHP or Hypertext Preprocessor and it was deployed to Windows Azure cloud platform. The test applications task is to call and load databases by controlled requests which creates, reads, updates and deletes data in an relatively large extent.The results shows that locale databases or databases in the same data center as the server generates the fastest response. The diffrence between NoSQL and SQL is practically nothing when it comes to simple requests. The type of data and the type of usage are major factors in the choice between the two databases.This paper works as a guidance in the choice of database for development of applications in the cloud. Keywords: SQL, NoSQL, databas, cloud, Azure, CouchDB, IrisCouch, database.com, databaseperformanceAbstrakt Som utvecklare av databasdrivna applikationer ställs man inför avgörande val när det kommer till databas, server och programmeringsspråk. För att resultatet ska bli en väl fungerande applikation krävs det att alla tekniker interagerar på ett bra sätt med varandra samt att de uppfyller vissa prestandakrav. Detta blir än viktigare när applikationen lyfts ut i molnet och svarstider spelar en stor roll.I arbetet undersöks olika databasers svarstider med hjälp av en testapplikation som är skriven i scriptspråketet PHP och driftsatt på Windows Azure-plattformen. Applikationens uppgift är att anropa och belasta databaser genom att genomföra kontrollerade operationer som skapar, hämtar, uppdaterar eller tar bort data i relativt stor omfattning.De databaser som praktiskt testats och utvärderats är Azure Table, Azure SQL, CouchDB, IrisCouch samt Database.com.Resultaten visar att lokala databaser, eller databaser inom samma datacenter som servern, generar de snabbaste responstiderna. Skillnaderna mellan NoSQL och SQL är i det närmaste försumbara när det handlar om enklare operationer. I valet mellan de två handlar det i mångt och mycket om vad databaserna ska användas till samt vilken typ av information som ska lagras i dem.Arbetet är tänkt att fungera som en vägledning i valet av databas vid utveckling av molntjänster. Nyckelord: SQL, NoSQL, databas, moln, Azure, CouchDB, IrisCouch, database.com, databasprestanda
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Vais, Zdeněk. "Návrh a implementace rozhraní pro zpracování rámců xPON." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413093.
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This thesis focuses on system for persistence of GPON communication. Theoretical part deals with problems of GPON and NG-PON optical networks, NoSQL database systems and MongoDB database. Practical part contains design of a database schema for MongoDB database and source code in programming languages Python and C# for working with this database. The thesis is finalized by performance testing, proving that the database design and source code implementation is capable of handling real world traffic.
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Ottosson, Love. "Cauldron: A Scalable Domain Specific Database for Product Data." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215710.
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This project investigated how NoSQL databases can be used together with a logical layer, instead of a relational database with separated backend logic, to search for products with customer specific constraints in an e-commerce scenario. The motivation behind moving from a relational database was the scalability issues and increased read latencies experienced as the data increased. The work resulted in a framework called Cauldron that uses pipelines a sequence of execution steps to expose its data stored in an in-memory key-value store and a document database. Cauldron uses write replication between distributed instances to increase read throughput at the cost of write latency. A product database with customer specific constraints was implemented using Cauldron to compare it against an existing solution based on a relational database. The new product database can serve search queries 10 times faster in the general case and up to 25 times faster in extreme cases compared to the existing solution.Projektet undersökte hur NoSQL databaser tillsammans med ett logiskt lager, istället för en relationsdatabas med separat backend logik, kan användas för att söka på produkter med kundunika restriktioner. Motivationen till att byta ut relationsdatabasen berodde på skalbarhetsproblem och långsammare svarstider när datamängden ökade. Arbetet resulterade i ett ramverk vid namn Cauldron som använder pipelines sammankopplade logiska steg för att exponera sin data från en minnesbunden nyckel-värde-databas och en dokumentdatabas. Cauldron använder replikering mellan distribuerade instanser för att öka läsgenomstömmningen på bekostnad av högre skrivlatenser. En produktdatabas med kundunika restriktioner implementerades med hjälp av Cauldron för att jämföra den mot en befintlig lösning baserad på en relationsdatabas. Den nya databasen kan besvara sökförfrågningar 10 gånger snabbare i normalfallen och upp till 25 gånger snabbare i extremfallen jämfört med den befintliga lösningen.
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Wheeler, Jared Thomas. "Extracting a Relational Database Schema from a Document Database." UNF Digital Commons, 2017. http://digitalcommons.unf.edu/etd/730.
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As NoSQL databases become increasingly used, more methodologies emerge for migrating from relational databases to NoSQL databases. Meanwhile, there is a lack of methodologies that assist in migration in the opposite direction, from NoSQL to relational. As software is being iterated upon, use cases may change. A system which was originally developed with a NoSQL database may accrue needs which require Atomic, Consistency, Isolation, and Durability (ACID) features that NoSQL systems lack, such as consistency across nodes or consistency across re-used domain objects. Shifting requirements could result in the system being changed to utilize a relational database. While there are some tools available to transfer data between an existing document database and existing relational database, there has been no work for automatically generating the relational database based upon the data already in the NoSQL system. Not taking the existing data into account can lead to inconsistencies during data migration. This thesis describes a methodology to automatically generate a relational database schema from the implicit schema of a document database. This thesis also includes details of how the methodology is implemented, and what could be enhanced in future works.
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Šoulák, Martin. "Systém pro analýzu a vyhodnocení jízd autoškoly." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363898.
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The objective of this master thesis is to design and develop a real-time storage system for geographic data from driving school trips. The system provides tools for analysis and evaluation of practice trips. This system is an extension of the DoAutoskoly.cz project which is described in the text. The next part contains an introduction to geographical data, spatial data and available databases with spatial extensions. The understanding to spatial databases is very important for the system design, an explanation of a solution for a database layer and implementation of major parts. Solution for a graphical view of the results and possible extensions of the system are described in the last part of this thesis.
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Warrén, Linus, and Daniel Tallkvist. "Time Series databaser för sensorsystem : En experimentell studie av prestanda för Time Series databaser för sensorsystem som grundas på: NoSQL eller RDBMS." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Datateknik och informatik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-43763.
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Purpose – The purpose of this study is to recommend a database and its belonging database model which is optimized for a sensor system. There is a lack of comparisons for databases and data models for bigger sensor systems. The study also brings scientific support for whom wishes to build a sensor system like the one which is included in this paper. Method – This paper starts with a literature study, which purpose is to choose the databases and the database models to be included in the comparison. To achieve the purpose of the study, a quantitative approach has been chosen. The study follows the steps that defines an experimental study within software development according to Shari Lawrence Pfleeger. Four predefined cases are used to compare the databases and the different database models which has been obtained in the literature study. Findings – The literature study shows that Time Series DBMS is the recommended database model to use for implementing sensor systems. The findings of the study also show that TimescaleDB is the preferable database over InfluxDB in four of four predefined cases. The null hypothesis which has been admitted is rejected and the alternative hypothesis is accepted at 1% significance level. Implications – The implications of the paper is to enhance the knowledge about Time Series DBMS, specifically of TimescaleDB and InfluxDB for sensor systems. The result can be implemented and used when resembling sensor systems are created. According to the result of the experiment it is shown that TimescaleDB is better than InfluxDB for sensor systems with similar datastructure. Limitations – Two Time Series DBMS (TimescaleDB and InfluxDB) were used in the experiments in this paper. The experiments was is carried out in Azure and is limited to 10 vCPU:s that a standard account have access to. There were not many beacons available to use for creating testdata. Files with corresponding data that the beacon sends out was created to simulate beacons. Keywords – Time Series DBMS, NoSQL, RDBMS, TimescaleDB, InfluxDB, Sensor systemsSyfte – I problembeskrivningen framgår att det finns brist på vetenskapligt underlag för vilken sorts databas som är optimal att använda för ett sensorsystem. Det saknas jämförelser av prestanda mellan olika databaser och datamodeller i större sensorsystem. Studiens syfte är: ”Att rekommendera en databas och tillhörande databasmodell som är optimerad för ett sensorsystem” Metod – Studien inleds med en litteraturstudie för att genom teorin välja databas och databasmodeller som ska ingå i studien. För att uppnå syftet har en kvantitativ ansats valts. Studien följer de steg som Shari Lawrence Pfleeger definierar som en experimentell studie inom mjukvaruutveckling. Fyra fördefinierade fall används för att jämföra databaserna med olika databasmodeller som erhållits i litteraturstudien. Resultat - Litteraturstudien visar att Time Series DBMS är den databasmodell som rekommenderas att användas i ett sensorsystem. Studiens resultat visar att TimescaleDB presterar bättre än InfluxDB i fyra av fyra fördefinierade fall. Nollhypotesen som har ställts upp förkastas och en mothypotes antas vid 1% signifikansnivå. Implikationer - Studiens implikationer är att öka och fylla vissa kunskapshål kring Time Series DBMS, specifikt TimescaleDB och InfluxDB för sensorsystem. Resultatet kan tillämpas och användas när liknande sensorsystem skall implementeras. Enligt experimentets resultat visar det att TimescaleDB är bättre än InfluxDB för sensorsystem med liknande struktur. Begränsningar – Två Time Series DBMS (TimescaleDB och InfluxDB) ingår i denna studie som experimenten utfördes på. Experimenten utföres i Azure och var begränsade av de 10 vCPU:erna ett standardkonto har tillgång till att använda. Det fanns inte tillgång till ett stort antal beacons för att generera data till experimenten, så filer med motsvarande data skapades för att simulera beacons. Nyckelord - Time Series DBMS, NoSQL, RDBMS, TimescaleDB, InfluxDB, Sensorsystem
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Ghourchian, Isabel. "Investigating Persistence Layers for Notifications." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254676.
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This work was carried out for Cisco at the Tail-f department. Cisco’s main focus is on network and telecommunication. The Tail-f department is the developer of a network service automatization product that allows customers to automate the process of adding, removing and manage their developed devices and services in their network. In the context of this network service, notifications will arise to notify operators when something has happened. The notifications are currently stored in a configurational database that is currently used for all the data in the network service. The customers have wished for more flexibility and functionality in terms of operating the notification data since they are limited in what queries they may perform in order to analyze their data. The purpose of this project is to find an alternative way of storing the notifications with better functionality and efficiency. A number of different databases were investigated with respect to the functionality and performance requirements of the system. A final storage system ElasticSearch was chosen. ElasticSearch provides flexible schema handling and complex queries which makes it a suitable choice that fulfills the customers’ needs. A generator and subscriber program were built in order to perform tests and insertion of notification data into ElasticSearch. The generator creates notifications manually and the subscriber receives them and performs some parsing and insertion into the storage. The queries and performance of ElasticSearch was measured. The query results show that the new system is able to perform much more complex queries than before such as range queries, filtering and full-text searches. The performance results show that the system is able to handle around 1000 notifications every other millisecond before the system will slow down. This is a sufficient number that satisfies the customers’ needs.Detta arbete utfördes för Cisco vid Tail-f avdelningen. Cisco fokuserar på nätoch telekommunikation. Tail-f är utvecklare av en automatiseringsprodukt för nätverk som gör det möjligt för kunder att automatisera processen att lägga till, ta bort och hantera sina utvecklade enheter och tjänster i deras nätverk. I samband med nätverkstjänsten kommer notifikationer att meddela operatörer när något har hänt.Meddelandena lagras för tillfället i en konfigurationsdatabas som för närvarande används för lagring av all data inom nätverkstjänsten. Kunderna har önskat efter mer flexibilitet och funktionalitet när det gäller att hantera datat eftersom de är begränsade i vilka sökfrågor de kan utföra för att analysera deras notifikationsdata.Syftet med detta projekt är att hitta ett alternativt sätt att lagra notifikationerna med bättre funktionalitet och effektivitet. Ett antal olika databaser undersöktes med avseende på systemets funktionalitet och prestandakrav. Ett slutgiltigt lagringssystem ElasticSearch valdes. ElasticSearch erbjuder flexibel schema-hantering och komplexa sökfrågor som gör det till ett lämpligt val som uppfyller kundernas behov. En generator och subscriber program utvecklades för att utföra test och införande av notifikationsdata i ElasticSearch. Generatorn skapar meddelanden manuellt och subscribern tar emot dem och utför viss parsing och insättning i lagringssystemet.Sökfrågor och prestanda för ElasticSearch mättes. Sökfrågans resultat visar att det nya systemet kan utföra mycket mer komplexa sökfrågor än tidigare, såsom intervall-sökningar, filtrering och full-text sökning. Resultatet visar att systemet kan hantera cirka 1000 notifikationer varannan millisekund innan systemet saktar ner. Detta är ett tillräckligt antal som uppfyller kundernas behov.
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Fjällid, Jimmy. "A Comparative Study of Databases for Storing Sensor Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-253772.
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More than 800 Zettabytes of data is predicted to be generated per year by the Internet of Things by 2021. Storing this data necessitates highly scalable databases. Many different data storage solutions exist that specialize in specific use cases, and designing a system to accept arbitrary sensor data while remaining scalable presents a challenge.The problem was approached through a comparative study of six common databases, inspecting documented features and evaluations, followed by the construction of a prototype system. Elasticsearch was found to be the best suited data storage system for the specific use case presented in this report, and a flexible prototype system was designed. No single database was determined to be best suited for sensor data in general, but with more specific requirements and knowledge of future use, a decision could be made.Över 800 Zettabytes av data är förutspått att genereras av Sakernas Internet vid år 2021. Lagring av denna data gör det nödvändigt med synnerligen skalbara databaser. Det finns många olika datalagringslösningar som specialiserar sig på specifika användningsområden, och att designa ett system som ska kunna ta emot godtycklig sensordata och samtidigt vara skalbar är en utmaning. Problemet angreps genom en jämförande studie av sex populära databaser som jämfördes utifrån dokumenterad funktionalitet och fristående utvärderingar. Detta följdes av utvecklingen ut av ett prototypsystem. Elasticsearch bedömdes vara bäst lämpad för det specifika användningsområde som presenteras i denna rapport, och ett flexibelt prototypsystem utvecklades. Inte en enda databas bedömdes vara bäst lämpad för att hantera sensordata i allmänhet, men med mer specifika krav och vetskap om framtida användning kan en databas väljas ut.
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Nilsson, Christoffer, and John Bengtson. "Storage and Transformation for Data Analysis Using NoSQL." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-142004.
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It can be difficult to choose the right NoSQL DBMS, and some systems lack sufficient research and evaluation. There are also tools for moving and transforming data between DBMS' in order to combine or use different systems for different use cases. We have described a use case, based on requirements related to the quality attributes Consistency, Scalability, and Performance. For the Performance attribute, focus is fast insertions and full-text search queries on a large dataset of forum posts. The evaluation was performed on two NoSQL DBMS' and two tools for transforming data between them. The DBMS' are MongoDB and Elasticsearch, and the transformation tools are NotaQL and Compose's Transporter. The purpose is to evaluate three different NoSQL systems, pure MongoDB, pure Elasticsearch and a combination of the two. The results show that MongoDB is faster when performing simple full-text search queries, but otherwise slower. This means that Elasticsearch is the primary choice regarding insertion and complex full-text search query performance. MongoDB is however regarded as a more stable and well-tested system. When it comes to scalability, MongoDB is better suited for a system where the dataset increases over time due to its simple addition of more shards. While Elasticsearch is better for a system which starts off with a large amount of data since it has faster insertion speeds and a more effective process for data distribution among existing shards. In general NotaQL is not as fast as Transporter, but can handle aggregations and nested fields which Transporter does not support. A combined system using MongoDB as primary data store and Elasticsearch as secondary data store could be used to achieve fast full-text search queries for all types of expressions, simple and complex.
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Henricsson, Robin. "Document Oriented NoSQL Databases : A comparison of performance in MongoDB and CouchDB using a Python interface." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5213.
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For quite some time relational databases, such as MySQL, Oracle and Microsoft SQL Server, have been used to store data for most applications. While they are indeed ACID compliant (meaning interrupted database transactions won't result in lost data or similar nasty surprises) and good at avoiding redundancy, they are difficult to scale horizontally (across multiple servers) and can be slow for certain tasks. With the Web growing rapidly, spawning enourmous, user-generated content websites such as Facebook and Twitter, fast databases that can handle huge amounts of data are a must. For this purpose new databases management systems collectively called NoSQL are being developed. This thesis explains NoSQL further and compares the write and retrieval speeds, as well as the space efficiency, of two database management systems from the document oriented branch of NoSQL called MongoDB and CouchDB, which both use the JavaScript Object Notation (JSON) to store their data within. The benchmarkings performed show that MongoDB is quite a lot faster than CouchDB, both when inserting and querying, when used with their respective Python libraries and dynamic queries. MongoDB also is more space efficient than CouchDB.
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Wännberg, Gottfrid, and André Forslöf. "Behovet av NoSQL-databaser hos Business Intelligence-företag : Studie som undersöker behovet av alternativa databaser inom Business Intelligence-området." Thesis, Umeå universitet, Institutionen för informatik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-171292.
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This study presents perceptions towards non-relational, or just NoSQL, databases in IT- and Business Intelligence companies, where we try to determine the need for NoSQL databases in these areas. Earlier studies indicate that the rise of Big Data will force companies to sooner or later expand their data storages to be able to handle the vast amount of data that will emerge, and to find ways to easily manage it. With this in mind, we wanted to determine why some Business Intelligence-companies still had not implemented non-relational databases in their systems, what this would implicate and how necessary it actually is. Our study included a case study at a Business Intelligence-company that still had not adopted these relatively new kinds of databases. First we used a survey to get an idea of what kind of knowledge concerning NoSQL-databases the employees at the company actually had, and to help us create questions for the interviews that would be the next step in our study. Through the interviews we had with three consultants and two developers we gathered a lot of interesting data concerning the company’s attitude towards implementing alternative databases in the system as a complement to their current SQL-based databases. For example, the low level of knowledge about NoSQL-databases of the employees showed a lot of preconceptions and assumptions about these alternative databases, that by extension led to a very skeptical attitude towards them. We learned however that the employees, especially the consultants, worried about the growing amount of data, which already was becoming laborious, and we estimate that companies that has not adopted a solution for this will eventually reach an inflection point where the amount of data will exceed the company’s ability to handle it.På grund av rådande pandemi (covid-19) hölls Studentkonferens Examensarbete i informatik 2020 genom videokonferens (Zoom)
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Josefsson, André. "Comparing the performance of relational and document databases for hierarchical geospatial data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231884.
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The aim of this degree project is to investigate alternatives to the relational database paradigm when storing hierarchical geospatial data. The document paradigm is found suitable and is therefore further examined. A benchmark suite is developed in order to test the relative performance of the paradigms for the relevant type of data. MongoDB and Microsoft SQL Server are chosen to represent the two paradigms in the benchmark. The results indicate that the document paradigm has potential when working with hierarchical structures. When adding geospatial elements to the data, the results are inconclusive.Det här examensarbetet ämnar undersöka alternativ till den relationella databasparadigmen för lagring av hierarkisk geospatial data. Dokumentparadigmen identiferas som särskilt lämplig och undersöks därför vidare. En benchmark-svit utvecklas för att undersöka de två paradigmens relativa prestanda vid lagring av den undersökta typen av data. MongoDB och Microsoft SQL Server väljs som representanter för de två paradigmen i benchmark-sviten. Resultaten indikerar att dokumentparadigmen har god potential för hierarkisk data. Inga tydliga slutsatser kan dock dras gällande den geospatiala aspekten.
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Guerreri, Sara. "Mongodb tra i database non relazionali - focus su Map-Reduce e gestione della memoria." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8809/.
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Perumal, Murugan Ananda Sentraya. "A Study of NoSQL and NewSQL databases for data aggregation on Big Data." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-143345.
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Sensor data analysis at Scania deal with large amount of data collected from vehicles. Each time a Scania vehicle enters a workshop, a large number of variables are collected and stored in a RDBMS at high speed. Sensor data is numeric and is stored in a Data Warehouse. Ad-hoc analyses are performed on this data using Business Intelligence (BI) tools like SAS. There are challenges in using traditional database that are studied to identify improvement areas. Sensor data is huge and is growing at a rapid pace. It can be categorized as BigData for Scania. This problem is studied to define ideal properties for a high performance and scalable database solution. Distributed database products are studied to find interesting products for the problem. A desirable solution is a distributed computational cluster, where most of the computations are done locally in storage nodes to fully utilize local machine’s memory, and CPU and minimize network load. There is a plethora of distributed database products categorized under NoSQL and NewSQL. There is a large variety of NoSQL products that manage Organizations data in a distributed fashion. NoSQL products typically have advantage as improved scalability and disadvantages like lacking BI tool support and weaker consistency. There is an emerging category of distributed databases known as NewSQL databases that are relational data stores and they are designed to meet the demand for high performance and scalability. In this paper, an exploratory study was performed to find suitable products among these two categories. One product from each category was selected based on comparative study for practical implementation and the production data was imported to the solutions. Performance for a common use case (median computation) was measured and compared. Based on these comparisons, recommendations were provided for a suitable distributed product for Sensor data analysis.