Relevant bibliographies by topics / NoSQL MongoDB

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'NoSQL MongoDB'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "NoSQL MongoDB"

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Renaldi, Renaldi, Billy Cahyo Santoso, Youzy Natasya, Steven Willian, and Fladianand Alfando. "Tinjauan Pustaka Sistematis terhadap Basis Data MongoDB." Jurnal Inovasi Informatika 5, no. 2 (September 30, 2020): 132–42. http://dx.doi.org/10.51170/jii.v5i2.79.

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Istilah NoSQL di dunia IT sudah mulai terkenal di bidang basis data. Basis data SQL dan NoSQL memilki perbedaan yang cukup signifikan.Model data yang digunakan basis data SQL yaitu berupa tabel, yang tersusun atas baris dan kolom. Basis data SQL manapun pasti model data yang sama dalam menyimpan arsip datanya, yaitu melalui tabel. Hal ini berbeda dengan basis data NoSQL. No SQL memilki arti non SQL atau not only SQL yang artinya ditujukan pada penggunaan model data alternatif selain tabular (relasi antar tabel). Tergantung basis datanya, basis data NoSQL bisa berupa dokumen, grafik ataupun nilai kunci. Salah basis data NoSQL yang sudah banyak dikenal orang yaitu MongoDB. MongoDB adalah basis data NoSQL yang bersifat document based, artinya hanya tersusun atas koleksi dan dokumen. Paper ini tertulis tentang karakteristik MongoDB, Kelebihan dan kekurangan MongoDB, Aplikasi yang sudah menggunakan MongoDB, serta beberapa contoh query yang di gunakan di MongoDB. Dengan paper ini, penulis berharap pembaca bisa mengerti dengan benar apa itu MongoDB serta implementasinya.
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Wahane, Deepa Suresh, and Prof Mayuri Dhondiba Dendge. "Analysis on NoSQL: MongoDB Tool." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (June 30, 2018): 1077–81. http://dx.doi.org/10.31142/ijtsrd13089.

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Xiang, Longgang, Xiaotian Shao, and Dehao Wang. "PROVIDING R-TREE SUPPORT FOR MONGODB." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 545–49. http://dx.doi.org/10.5194/isprsarchives-xli-b4-545-2016.

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Supporting large amounts of spatial data is a significant characteristic of modern databases. However, unlike some mature relational databases, such as Oracle and PostgreSQL, most of current burgeoning NoSQL databases are not well designed for storing geospatial data, which is becoming increasingly important in various fields. In this paper, we propose a novel method to provide R-tree index, as well as corresponding spatial range query and nearest neighbour query functions, for MongoDB, one of the most prevalent NoSQL databases. First, after in-depth analysis of MongoDB’s features, we devise an efficient tabular document structure which flattens R-tree index into MongoDB collections. Further, relevant mechanisms of R-tree operations are issued, and then we discuss in detail how to integrate R-tree into MongoDB. Finally, we present the experimental results which show that our proposed method out-performs the built-in spatial index of MongoDB. Our research will greatly facilitate big data management issues with MongoDB in a variety of geospatial information applications.
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Xiang, Longgang, Xiaotian Shao, and Dehao Wang. "PROVIDING R-TREE SUPPORT FOR MONGODB." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 545–49. http://dx.doi.org/10.5194/isprs-archives-xli-b4-545-2016.

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Supporting large amounts of spatial data is a significant characteristic of modern databases. However, unlike some mature relational databases, such as Oracle and PostgreSQL, most of current burgeoning NoSQL databases are not well designed for storing geospatial data, which is becoming increasingly important in various fields. In this paper, we propose a novel method to provide R-tree index, as well as corresponding spatial range query and nearest neighbour query functions, for MongoDB, one of the most prevalent NoSQL databases. First, after in-depth analysis of MongoDB’s features, we devise an efficient tabular document structure which flattens R-tree index into MongoDB collections. Further, relevant mechanisms of R-tree operations are issued, and then we discuss in detail how to integrate R-tree into MongoDB. Finally, we present the experimental results which show that our proposed method out-performs the built-in spatial index of MongoDB. Our research will greatly facilitate big data management issues with MongoDB in a variety of geospatial information applications.
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Jain, Vidushi, and Aviral Upadhyay. "MongoDB and NoSQL Databases." International Journal of Computer Applications 167, no. 10 (June 15, 2017): 16–20. http://dx.doi.org/10.5120/ijca2017914385.

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Andor, C. F. "Performance Benchmarking for NoSQL Database Management Systems." Studia Universitatis Babeș-Bolyai Informatica 66, no. 1 (July 1, 2021): 23. http://dx.doi.org/10.24193/subbi.2021.1.02.

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NoSQL database management systems are very diverse and are known to evolve very fast. With so many NoSQL database options available nowadays, it is getting harder to make the right choice for certain use cases. Also, even for a given NoSQL database management system, performance may vary significantly between versions. Database performance benchmarking shows the actual performance for different scenarios on different hardware configurations in a straightforward and precise manner. This paper presents a NoSQL database performance study in which two of the most popular NoSQL database management systems (MongoDB and Apache Cassandra) are compared, and the analyzed metric is throughput. Results show that Apache Cassandra outperformes MongoDB in an update heavy scenario only when the number of operations is high. Also, for a read intensive scenario, Apache Cassandra outperformes MongoDB only when both number of operations and degree of parallelism are high.
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Zhao, Yan. "Research on MongoDB Design and Query Optimization in Vehicle Management Information System." Applied Mechanics and Materials 246-247 (December 2012): 418–22. http://dx.doi.org/10.4028/www.scientific.net/amm.246-247.418.

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NoSQL database is the broad definition of non-relational database. MongoDB is one of the most popular NoSQL database nowadays, and it is a schema-free and document oriented database, which has great query performance with huge amount of data and great scalability. More and more companies have adopted MongoDB, as increasingly large scale data is being stored in MongoDB, design philosophy and query optimization issues become growing concerns. This paper attempts to give the data storage structures of MongoDB on vehicle management information system. Based on this system, this paper gives two design philosophy and five different query optimization methods for MongoDB and gives the key code and diagrams of MongoDB optimization methods.
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Tunardi, Yovita, and Rita Layona. "Nosql Technology In Android Based Mobile Chat Application Using Mongodb." ComTech: Computer, Mathematics and Engineering Applications 5, no. 2 (December 1, 2014): 553. http://dx.doi.org/10.21512/comtech.v5i2.2180.

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Along with the development of data storage technology which previously using relational concept began to change to the non-relational concept or sometimes referred to as the term NoSQL technology. Data storage in NoSQL is no longer based on the relations between tables but using another methods, one of them is document-oriented. This method was applied specifically in MongoDB. This concept brings new hope because oftheir superiority that can handle very large data with promising performance and is perfect for agile system development. The purpose of this research was to measure the performance NoSQL, especially MongoDB with implemented it in a Android based mobile chat application. This research uses three methods, analysis method including literature study, analysis of similar application, questionnaires, design method using Agile SofwareDevelopment, and evaluation method including eight golden rules, analysis of similar application, questionnaires, and interview. The results of this research is a mobile chat application that uses MongoDB as the data storage technology. Through this research can be drawn the conclusion that NoSQL technology implementation, MongoDB, give special advantages like lighter data storage and faster data access.
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Gupta, Sangeeta. "Performance Evaluation of Unstructured PBRA for Bigdata with Cassandra and MongoDB in Cloud." International Journal of Cloud Applications and Computing 8, no. 3 (July 2018): 48–59. http://dx.doi.org/10.4018/ijcac.2018070104.

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In this article, performance evaluation of web collection data in data stores, such as NoSQL-Cassandra and MongoDB is presented, yielding scalability of applications. In addition to scalability, security of NoSQL databases remains highly unproved. It is noteworthy that existing works in the area of cloud with NoSQL focus on either scalability or security but not both aspects. Also, security, if provided, is at minor interface levels. In this article, the PBRA system is designed to deal with highly unstructured big data emerging from the twitter social networking service, which is new of its kind to strengthen the bigdata security. PBRA is Passphrase Based REST API model where the REST API methods are integrated with the user generated passphrase in addition to the private key for a set of records of user desirable number before storing into the Cassandra and MongoDB databases. Results are presented to illustrate the same for nearly 1 million records and the efficiency of Cassandra over MongoDB is observed. It is observed from the results that though the time taken to load and retrieve bulk data records is higher than dealing with cipher text, Cassandra performs better than MongoDB with the proposed security model.
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Kriestanto, Danny, and Alif Benden Arnado. "IMPLEMENTASI WEBSITE PENCARIAN KOS DENGAN NoSQL." JIKO (Jurnal Informatika dan Komputer) 2, no. 2 (October 12, 2017): 103. http://dx.doi.org/10.26798/jiko.2017.v2i2.66.

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The new technology of database has moved forward the relational databases. Now, the massive and unstructured data encourage experts to create a new type of database without using query. One of this technology is called NoSQL (Not Only SQL). One of the developing RDBMS that using this technique is MongoDB, which already supporting data storage technology that is no longer need for structured tables and rigid-typed of data. The schema was made flexible to handle the changes of data. The MongoDB data collecting characteristics in the form of arrays is considered suitable for the implementation of boarding house searching where each of the boarding houses have their own scenario structures. MongoDB also supports several programming language, including PHP with Bootstrap material as interface. The results of the research showed that there are alot of difference in implementing a NoSQL database with the regular relational one. NoSQL databases considered alot more complicated in structure, data type, even the CRUD system. The results also showed that in order to view an array inside another array will need two processes.
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Dissertations / Theses on the topic "NoSQL MongoDB"

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Arvidsson, Andreas, and Jörgen Bygdemark. "JÄMFÖRELSE MELLAN ORACLE RDBMS, ORACLE NOSQL OCH MONGODB." Thesis, Umeå universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-163179.

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Databases are present everywhere in our modern society and the amount of data that have to be stored is constantly increasing, which means that it’s now more important than ever to be able to handle massive data sets e‚ffectively. NoSQL databases2 were developed to solve this problem by efficiently storing large amounts of data and enable fast access to that data. Since NoSQL databases only became popular within the last ten years, they haven’t been as well researched as relational databases. An in-depth evaluation is carried out on six distinct features, where one part is comparative performance tests. Th‘e other features are: scalability, consistency, availability, durability and reliability. MongoDB and Oracle NoSQL are the NoSQL databases used and together with Oracle RDBMS as relational database make up the basis for a comparative study of the above mentioned features.Th‘e results showed that there are big diff‚erences between how data is handled in NoSQL compared to relational databases that will aff‚ect the choice of database, e.g. that NoSQL tends to prioritize that clients can reach the database over non-contradictory data and lowering the demands on transaction management to increase performance and storage capacity. Furthermore, the performance tests showed that both NoSQL databases performed be‹er than the relational database regardless of the data set size. MongoDB was clearly the fastest on reading operations, while Oracle NoSQL performed write operations the fastest most of the time. Both NoSQL databases are impacted less by a growing data set than the relational database for both read and write operations.
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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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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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Wester, Alfred, and Olof Fredriksson. "Jämförelse av Mysql och MongoDb." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2310.

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Speed is a very important factor in websites and other types of applications and almost all applications stores some type of data, normally in a database. For an example a blog typically saves users, posts and comments. There’s a high risk that as the amount of data in the database grows, the time for inserting and requesting specific data increases. If it takes more than some seconds to view a specific page, a user will normally leave the site. However, it’s a fact that the database will grow while the application will become more popular but it’s possible to save a lot of time if using right database, and structure. In this thesis MongoDB and MySQL will be compared with focus on time consumption. SQL (Structured Query Language) is the language which most databases use. This kind of database stores data in structured tables and noting can be added to them if the type of data is incorrect. SQL also support relations between tables. MySQL is a very popular relational database management system (RDBMS) which for example websites frequently makes use of. NoSQL is a new type of databases where the data is stored in collections without any kind of structure, unlike the well known SQL databases where the data is stored in structured tables. Because of the non-structure, these types of databases are designed to be fast and scalable over multiple machines. Mongodb is a such kind of NoSql-database. Tests has been done both on inserting and processing when handling up to 4 millions entities, MongoDB performs better in almost every test. Results shows that the processing time is shorter using MongoDb in the cases that this thesis is covering, and that it’s possible to implement a much fast application when using MongoDb instead of Mysql as database.
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Nirfelt, Sebastian. "Replikation: Prestanda med MongoDB." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20940.

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Förmågan att lagra data är en stor bidragande faktor till att vetenskapen ständigt rört sig framåt. Under några tusen år har människan utvecklats från att lagra data på grottväggar till hårddiskar och kraven på prestanda, tillgång och felsäkerhet ökar i rasande takt. För att hantera data i det moderna samhället utvecklas ständigt nya metoder och en av dessa metoder är replikation. Den här undersökningen testar hur replikation påverkar prestandan i en distribuerad MongoDB-lösning. Testerna i undersökningen är automatiserade och körs mot databasen i olika konfigurationer för att se hur prestandan förändras.
The ability to store data is a contributing factor in making science constantly move forward. In a few thousand years man has evolved from storing information on cave walls to hard drives and requirements in performance, availability and fault tolerance are rapidly increasing. To manage information in modern society new methods are constantly evolving and one of these methods is replication. This study tests how replication affects the performance in a distributed MongoDB solution. The tests in this survey are automated and run against the database in different configurations to see how performance changes.
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Ankit, Bajpai. "SQL versus MongoDB from an application development point of view." Kansas State University, 2014. http://hdl.handle.net/2097/18816.

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Master of Science
Department of Computing and Information Sciences
Doina Caragea
There are many formats in which digital information is stored in order to share and re-use it by different applications. The web can hardly be called old and already there is huge research going on to come up with better formats and strategies to share information. Ten years ago formats such as XML, CSV were the primary data interchange formats. And these formats were huge improvements over SGML (Standard Generalized Markup Language). It’s no secret that in last few years there has been a huge transformation in the world of data interchange. More lightweight, bandwidth-non-intensive JSON has taken over traditional formats such as XML and CSV. BigData is the next big thing in computer sciences and JSON has emerged as a key player in BigData database technologies. JSON is the preferred format for web-centric, “NoSQL” databases. These databases are intended to accommodate massive scalability and designed to store data which does not follow any columnar or relational model. Almost all modern programming languages support object oriented concepts, and most of the entity modeling is done in the form of objects. JSON stands for Java Script object notation and as the name suggests this object oriented nature helps modeling entities very naturally. And hence the exchange of data between the application logic and database is seamless. The aim of this report is to develop two similar applications, one with traditional SQL as the backend, and the other with a JSON supporting MongoDB. I am going to build real life functionalities and test the performance of various queries. I will also discuss other aspects of databases such as building a Full Text Index (FTI) and search optimization. Finally I will plot graphs to study the trend in execution time of insertion, deletion, joins and co- relational queries with and without indexes for SQL database, and compare them with the execution trend of MongoDB queries.
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Agena, Barbara Tieko. "Acesso a dados baseado em ontologias com NoSQL." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-23012018-132444/.

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O acesso a dados baseado em ontologia (OBDA, de Ontology-Based Data Access) propõe facilitar ao usuário acesso a dados sem o conhecimento específico de como eles estão armazenados em suas fontes. Para isso, faz-se uso de uma ontologia como camada conceitual de alto nível, explorando sua capacidade de descrever o domínio e lidar com a incompletude dos dados. Atualmente, os sistemas NoSQL (Not Only SQL) estão se tornando populares, oferecendo recursos que os sistemas de bancos de dados relacionais não suportam. Desta forma, surgiu a necessidade dos sistemas OBDA se moldarem a estes novos tipos de bancos de dados. O objetivo desta pesquisa é propor uma arquitetura nova para sistemas OBDA possibilitando o acesso a dados em bancos de dados relacionais e bancos de dados NoSQL. Para tal, foi proposta a utilização de um mapeamento mais simples responsável pela comunicação entre ontologia e bancos de dados. Foram construídos dois protótipos de sistemas OBDA para sistemas NoSQL e sistemas de bancos de dados relacional para uma validação empírica da arquitetura proposta neste trabalho.
Ontology-based data access (OBDA) proposes to facilitate user access to data without specific knowledge of how they are stored in their sources. For this, an ontology is used as a high level conceptual layer, exploring its capacity to describe the domain and deal with the incompleteness of the data. Currently, NoSQL (Not Only SQL) systems are becoming popular, offering features that relational database systems do not support. In this way, the need arose for shaping OBDA systems to deal with these new types of databases. The objective of this research is to propose a new architecture for OBDA systems allowing access to data in relational databases and NoSQL databases. For this, we propose the use of a simpler mapping responsible for the communication between ontology and databases. Two OBDA system prototypes were constructed: one for NoSQL systems and one for relational database systems for an empirical validation.
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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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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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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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Books on the topic "NoSQL MongoDB"

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Peter, Membrey, Hawkins Tim, and SpringerLink (Online service), eds. The Definitive Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing. Berkeley, CA: Eelco Plugge, Tim Hawkins, Peter Membrey, 2010.

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NoSQL with MongoDB in 24 hours. Sams Publishing, 2014.

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Membrey, Peter, Eelco Plugge, and DUPTim Hawkins. The Definitive Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing. Apress, 2011.

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Bierer, Doug. MongoDB 4 Quick Start Guide: Learn the skills you need to work with the world's most popular NoSQL database. Packt Publishing, 2018.

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Book chapters on the topic "NoSQL MongoDB"

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Edward, Shakuntala Gupta, and Navin Sabharwal. "NoSQL." In Practical MongoDB, 13–23. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-0647-8_2.

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Sharma, Manish. "Why NoSQL?" In Cosmos DB for MongoDB Developers, 1–10. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3682-6_1.

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Kleuker, Stephan. "NoSQL mit MongoDB und Java." In Grundkurs Datenbankentwicklung, 299–326. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-12338-3_15.

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Das, Prashanta Kumar. "Tutorial on MongoDB." In NoSQL: Database for Storage and Retrieval of Data in Cloud, 401–4. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2016] |Includes bibliographical references and index.: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315155579-24.

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Haughian, Gerard, Rasha Osman, and William J. Knottenbelt. "Benchmarking Replication in Cassandra and MongoDB NoSQL Datastores." In Lecture Notes in Computer Science, 152–66. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44406-2_12.

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Sudhakar and Shivendra Kumar Pandey. "An Approach to Improve Load Balancing in Distributed Storage Systems for NoSQL Databases: MongoDB." In Advances in Intelligent Systems and Computing, 529–38. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7871-2_51.

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Michel, Franck, Catherine Faron-Zucker, and Johan Montagnat. "Bridging the Semantic Web and NoSQL Worlds: Generic SPARQL Query Translation and Application to MongoDB." In Lecture Notes in Computer Science, 125–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-58664-8_5.

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Habyarimana, Ephrem, and Sofia Michailidou. "Genomics Data." In Big Data in Bioeconomy, 69–76. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_6.

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AbstractIn silico prediction of plant performance is gaining increasing breeders’ attention. Several statistical, mathematical and machine learning methodologies for analysis of phenotypic, omics and environmental data typically use individual or a few data layers. Genomic selection is one of the applications, where heterogeneous data, such as those from omics technologies, are handled, accommodating several genetic models of inheritance. There are many new high throughput Next Generation Sequencing (NGS) platforms on the market producing whole-genome data at a low cost. Hence, large-scale genomic data can be produced and analyzed enabling intercrosses and fast-paced recurrent selection. The offspring properties can be predicted instead of manually evaluated in the field . Breeders have a short time window to make decisions by the time they receive data, which is one of the major challenges in commercial breeding. To implement genomic selection routinely as part of breeding programs, data management systems and analytics capacity have therefore to be in order. The traditional relational database management systems (RDBMS), which are designed to store, manage and analyze large-scale data, offer appealing characteristics, particularly when they are upgraded with capabilities for working with binary large objects. In addition, NoSQL systems were considered effective tools for managing high-dimensional genomic data. MongoDB system, a document-based NoSQL database, was effectively used to develop web-based tools for visualizing and exploring genotypic information. The Hierarchical Data Format (HDF5), a member of the high-performance distributed file systems family, demonstrated superior performance with high-dimensional and highly structured data such as genomic sequencing data.
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Werner, Aleksandra, and Małgorzata Bach. "NoSQL E-learning Laboratory—Interactive Querying of MongoDB and CouchDB and Their Conversion to a Relational Database." In Advances in Intelligent Systems and Computing, 581–92. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67792-7_56.

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Tidke, Sonali. "MonogDB." In Privacy and Security Policies in Big Data, 64–91. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2486-1.ch004.

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MongoDB is a NoSQL type of database management system which does not adhere to the commonly used relational database management model. MongoDB is used for horizontal scaling across a large number of servers which may have tens, hundreds or even thousands of servers. This horizontal scaling is performed using sharding. Sharding is a database partitioning technique which partitions large database into smaller parts which are easy to manage and faster to access. There are hundreds of NoSQL databases available in the market. But each NoSQL product is different in terms of features, implementations and behavior. NoSQL and RDBMS solve different set of problems and have different requirements. MongoDB has a powerful query language which extends SQL to JSON enabling developers to take benefit of power of SQL and flexibility of JSON. Along with support for select/from/where type of queries, MongoDB supports aggregation, sorting, joins as well as nested array and collections. To improve query performance, indexes and many more features are also available.
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Conference papers on the topic "NoSQL MongoDB"

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Gu, Yunhua, Shu Shen, Jin Wang, and Jeong-Uk Kim. "Application of NoSQL database MongoDB." In 2015 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW). IEEE, 2015. http://dx.doi.org/10.1109/icce-tw.2015.7216831.

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Hou, Boyu, Kai Qian, Lei Li, Yong Shi, Lixin Tao, and Jigang Liu. "MongoDB NoSQL Injection Analysis and Detection." In 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud). IEEE, 2016. http://dx.doi.org/10.1109/cscloud.2016.57.

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Parker, Zachary, Scott Poe, and Susan V. Vrbsky. "Comparing NoSQL MongoDB to an SQL DB." In the 51st ACM Southeast Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2498328.2500047.

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Sachdeva, Vrinda, and Sachin Gupta. "Basic NOSQL Injection Analysis And Detection On MongoDB." In 2018 International Conference on Advanced Computation and Telecommunication (ICACAT). IEEE, 2018. http://dx.doi.org/10.1109/icacat.2018.8933707.

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Stanescu, Liana, Marius Brezovan, and Dumitru Dan Burdescu. "Automatic Mapping of MySQL Databases to NoSQL MongoDB." In 2016 Federated Conference on Computer Science and Information Systems. IEEE, 2016. http://dx.doi.org/10.15439/2016f45.

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Andreoli, Remo, Tommaso Cucinotta, and Dino Pedreschi. "RT-MongoDB: A NoSQL Database with Differentiated Performance." In 11th International Conference on Cloud Computing and Services Science. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010452400770086.

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Gomes, Carlos, Eduardo Tavares, and Meuse Nogueira De O. Junior. "Energy Consumption Evaluation of NoSQL DBMSs." In XV Workshop em Desempenho de Sistemas Computacionais e de Comunicação. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/wperformance.2016.9729.

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Over the years, NoSQL Database Management Systems (DBMS) have been adopted as an alternative to the constraints of relational/SQL DBMSs. In order to demonstrate their feasibility, works have evaluated NoSQL DBMSs regarding some performance metrics, but energy consumption has not been assessed. Indeed, energy consumption is an issue that should not be neglected due to the rise of energy costs and environmental sustainability. This paper presents a peformance and energy consumption evaluation of NoSQL DBMSs, more specifically, Cassandra (column), MongoDB (document-oriented), Redis (key-value). Experiments are based on YCSB benchmark, and results demonstrate energy consumption can vary significantly among the assessed DBMSs for different commands (e.g., read) and workloads.
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Gu, Yunhua, Xing Wang, Shu Shen, Sai Ji, and Jin Wang. "Analysis of data replication mechanism in NoSQL database MongoDB." In 2015 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW). IEEE, 2015. http://dx.doi.org/10.1109/icce-tw.2015.7217033.

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Gu, Yunhua, Xing Wang, Shu Shen, Jin Wang, and Jeong-Uk Kim. "Analysis of data storage mechanism in NoSQL database MongoDB." In 2015 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW). IEEE, 2015. http://dx.doi.org/10.1109/icce-tw.2015.7217036.

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Kumar, Jitender, and Varsha Garg. "Security analysis of unstructured data in NOSQL MongoDB database." In 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN). IEEE, 2017. http://dx.doi.org/10.1109/ic3tsn.2017.8284495.

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