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Journal articles on the topic 'Database management systems (DBMSs)'

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Published: 2 June 2025

Last updated: 31 July 2025

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1

Aljwari, Fatima Khalil. "External vs. Internal: An Essay on Machine Learning Agents for Autonomous Database Management Systems." European Journal of Computer Science and Information Technology 10, no. 5 (2022): 24–31. http://dx.doi.org/10.37745/ejcsit.2013/vol10n52431.

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There are many possible ways to configure database management systems (DBMSs) have challenging to manage and set.The problem increased in large-scale deployments with thousands or millions of individual DBMS that each have their setting requirements. Recent research has explored using machine learning-based (ML) agents to overcome this problem's automated tuning of DBMSs. These agents extract performance metrics and behavioral information from the DBMS and then train models with this data to select tuning actions that they predict will have the most benefit. This paper discusses two engineerin

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Pavlo, Andrew, Matthew Butrovich, Lin Ma, et al. "Make your database system dream of electric sheep." Proceedings of the VLDB Endowment 14, no. 12 (2021): 3211–21. http://dx.doi.org/10.14778/3476311.3476411.

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Database management systems (DBMSs) are notoriously difficult to deploy and administer. Self-driving DBMSs seek to remove these impediments by managing themselves automatically. Despite decades of DBMS auto-tuning research, a truly autonomous, self-driving DBMS is yet to come. But recent advancements in artificial intelligence and machine learning (ML) have moved this goal closer. Given this, we present a system implementation treatise towards achieving a self-driving DBMS. We first provide an overview of the NoisePage self-driving DBMS that uses ML to predict the DBMS's behavior and optimize

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Song, Jiansen, Wensheng Dou, Yu Gao, et al. "Detecting Metadata-Related Logic Bugs in Database Systems via Raw Database Construction." Proceedings of the VLDB Endowment 17, no. 8 (2024): 1884–97. http://dx.doi.org/10.14778/3659437.3659445.

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Database Management Systems (DBMSs) are widely used to efficiently store and retrieve data. DBMSs usually support various metadata, e.g., integrity constraints for ensuring data integrity and indexes for locating data. DBMSs can further utilize these metadata to optimize query evaluation. However, incorrect metadata-related optimizations can introduce metadata-related logic bugs, which can cause a DBMS to return an incorrect query result for a given query. In this paper, we propose a general and effective testing approach, Raw database construction (Radar), to detect metadata-related logic bug

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Carvalho, Nuno, Alfranio Jr., José Pereira, Luís Rodrigues, Rui Oliveira, and Susana Guedes. "On the Use of a Reflective Architecture to Augment Database Management Systems." JUCS - Journal of Universal Computer Science 13, no. (8) (2007): 1110–35. https://doi.org/10.3217/jucs-013-08-1110.

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The Database Management System (DBMS) used to be a commodity software component, with well known standard interfaces and semantics. However, the performance and reliability expectations being placed on DBMSs have increased the demand for a variety add-ons, that augment the functionality of the database in a wide range of deployment scenarios, offering support for features such as clustering, replication, and self-management, among others. A well known software engineering approach to systems with such requirements is reflection. Unfortunately, standard reflective interfaces in DBMSs are very l

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Camilleri, Carl, Joseph G. Vella, and Vitezslav Nezval. "HTAP With Reactive Streaming ETL." Journal of Cases on Information Technology 23, no. 4 (2021): 1–19. http://dx.doi.org/10.4018/jcit.20211001.oa10.

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In database management systems (DBMSs), query workloads can be classified as online transactional processing (OLTP) or online analytical processing (OLAP). These often run within separate DBMSs. In hybrid transactional and analytical processing (HTAP), both workloads may execute within the same DBMS. This article shows that it is possible to run separate OLTP and OLAP DBMSs, and still support timely business decisions from analytical queries running off fresh transactional data. Several setups to manage OLTP and OLAP workloads are analysed. Then, benchmarks on two industry standard DBMSs empir

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Ansari, Sakil Ahmad, and Jaychand Vishwakarma. "Survey on Database Concurrency Control in Multilevel Secure Database Management Systems." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 4 (2018): 105. http://dx.doi.org/10.23956/ijarcsse.v8i4.645.

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Transactions are vital for database management systems (DBMSs) because they provide transparency to concurrency and failure. Concurrent execution of transactions may lead to contention for access to data, which in a multilevel secure DBMS (MLSIDBMS) may lead to insecurity. In this paper we examine security issues involved in database concurrency control for MLS/DBMSs and show how a scheduler can affect security. We introduce Data Conflict Security; (DC-Security) a property that implies a system is free of convert channels due to contention for access to data. We present a definition of DC Secu

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Zhong, Suyang, and Manuel Rigger. "Understanding and Reusing Test Suites Across Database Systems." Proceedings of the ACM on Management of Data 2, no. 6 (2024): 1–26. https://doi.org/10.1145/3698829.

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Database Management System (DBMS) developers have implemented extensive test suites to test their DBMSs. For example, the SQLite test suites contain over 92 million lines of code. Despite these extensive efforts, test suites are not systematically reused across DBMSs, leading to wasted effort. Integration is challenging, as test suites use various test case formats and rely on unstandardized test runner features. We present a unified test suite, SQuaLity, in which we integrated test cases from three widely-used DBMSs, SQLite, PostgreSQL, and DuckDB. In addition, we present an empirical study t

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Gu, Long, Si Liu, Tiancheng Xing, Hengfeng Wei, Yuxing Chen, and David Basin. "IsoVista: Black-Box Checking Database Isolation Guarantees." Proceedings of the VLDB Endowment 17, no. 12 (2024): 4325–28. http://dx.doi.org/10.14778/3685800.3685866.

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Transactional isolation is critical to the functional correctness of database management systems (DBMSs). Much effort has recently been devoted to finding isolation bugs and validating isolation fulfilment in production DBMSs. However, there are still challenges that existing isolation checkers have not yet fully addressed. For instance, they may overlook bugs, incur high checking overhead, and return hard-to-understand counterexamples. We present IsoVista, the first black-box isolation checking system that encompasses all the following features. It builds on faithful characterizations of a ra

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Taipalus, Toni, Hilkka Grahn, Hannu Turtiainen, and Andrei Costin. "Utilizing Vector Database Management Systems in Cyber Security." European Conference on Cyber Warfare and Security 23, no. 1 (2024): 560–65. http://dx.doi.org/10.34190/eccws.23.1.2220.

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The rising popularity of phenomena such as ubiquitous computing and IoT poses increasingly high demands for data management, and it is not uncommon that database management systems (DBMS) must be capable of reading and writing hundreds of operations per second. Vector DBMSs (VDBMS) are novel products that focus on the management of vector data and can alleviate data management pressures by storing data objects such as logs, system calls, emails, network flow data, and memory dumps in feature vectors that are computationally efficient in both storage and information retrieval. VDMBSs allow effi

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Zhang, Chi, and Manuel Rigger. "Constant Optimization Driven Database System Testing." Proceedings of the ACM on Management of Data 3, no. 1 (2025): 1–24. https://doi.org/10.1145/3709674.

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Logic bugs are bugs that can cause database management systems (DBMSs) to silently produce incorrect results for given queries. Such bugs are severe, because they can easily be overlooked by both developers and users, and can cause applications that rely on the DBMSs to malfunction. In this work, we propose Constant-Optimization-Driven Database Testing (CODDTest) as a novel approach for detecting logic bugs in DBMSs. This method draws inspiration from two well-known optimizations in compilers: constant folding and constant propagation. Our key insight is that for a certain database state and q

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Lim, Wan Shen, Lin Ma, William Zhang, Matthew Butrovich, Samuel Arch, and Andrew Pavlo. "Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems." Proceedings of the VLDB Endowment 17, no. 11 (2024): 3680–93. http://dx.doi.org/10.14778/3681954.3682030.

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Autonomous database management systems (DBMSs) aim to optimize themselves automatically without human guidance. They rely on machine learning (ML) models that predict their run-time behavior to evaluate whether a candidate configuration is beneficial without the expensive execution of queries. However, the high cost of collecting the training data to build these models makes them impractical for real-world deployments. Furthermore, these models are instance-specific and thus require retraining whenever the DBMS's environment changes. State-of-the-art methods spend over 93% of their time runnin

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Diallo, B., J. M. Travere, and B. Mazoyer. "A Review of Database Management Systems Suitable for Neuroimaging." Methods of Information in Medicine 38, no. 02 (1999): 132–39. http://dx.doi.org/10.1055/s-0038-1634174.

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AbstractThis study comprises a technical assessment of Database Management Systems (DBMS), which may be of use in the analysis of data obtained from human brain mapping procedures. Due to the large expansion of the neuroimaging field, the use of specialized database software to store and process neuroimages and their attached components is inevitable. The advent of multiple software products, a wealth of technical terms and a wide variety of other applications make the choice of a suitable program sometimes difficult. Through the inclusion of some basic and pertinent criteria (e.g., performanc

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Yi, Mon Win. "Object Oriented DBMSs using GIS Data." Dagon University Research Journal Vol.5, no. 2013 (2019): Pg.155–163. https://doi.org/10.5281/zenodo.3545545.

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Data management and organization have become so complex and challenging in today’s electronic age of information. In the last decade major changes have occurred in the database domain, as the result of increased interest to non-traditional database applications such as multimedia, office automation, CAD, CASE, GIS, Web databases, and others. In contrast to the relational era, the current database world is more diverse and showing contradictory tendencies. On the one hand, vendors of popular relational database management systems (DBMS), such as IBM, Informix and Oracle, extend their prod

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Shahidinejad, Javad, Mohsen Kalantari, and Abbas Rajabifard. "3D Cadastral Database Systems—A Systematic Literature Review." ISPRS International Journal of Geo-Information 13, no. 1 (2024): 30. http://dx.doi.org/10.3390/ijgi13010030.

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Cadastral databases have been used for over 20 years, but most contain 2D data. The increasing presence of high-rise buildings with modern architecture complicates the process of determining property rights, restrictions, and responsibilities. It is, therefore, necessary to develop an efficient system for storing and managing multidimensional cadastral data. While there have been attempts to develop 3D cadastral database schemas, a comprehensive solution that meets all the requirements for effective data storage, manipulation, and retrieval has not yet been presented. This study aims to analys

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Li, Tianyu, Matthew Butrovich, Amadou Ngom, Wan Shen Lim, Wes McKinney, and Andrew Pavlo. "Mainlining databases." Proceedings of the VLDB Endowment 14, no. 4 (2020): 534–46. http://dx.doi.org/10.14778/3436905.3436913.

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The proliferation of modern data processing tools has given rise to open-source columnar data formats. These formats help organizations avoid repeated conversion of data to a new format for each application. However, these formats are read-only, and organizations must use a heavy-weight transformation process to load data from on-line transactional processing (OLTP) systems. As a result, DBMSs often fail to take advantage of full network bandwidth when transferring data. We aim to reduce or even eliminate this overhead by developing a storage architecture for in-memory database management syst

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Yijie Weng and Jianhao Wu. "Database management systems for artificial intelligence: Comparative analysis of postgre SQL and MongoDB." World Journal of Advanced Research and Reviews 25, no. 2 (2025): 2336–42. https://doi.org/10.30574/wjarr.2025.25.2.0586.

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The rapid evolution of artificial intelligence (AI) has amplified the need for efficient database management systems (DBMS) to handle the growing volume, variety, and velocity of data. PostgreSQL, a robust relational database, and MongoDB, a leading NoSQL solution, are two widely adopted DBMSs in AI applications, each offering unique advantages. This paper provides a comprehensive comparative analysis of PostgreSQL and MongoDB, focusing on their suitability for AI use cases. Key evaluation criteria include data modeling, query complexity, scalability, ACID compliance, indexing, and integration

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Wen, Shihao, Peng Jia, Pin Yang, and Chi Hu. "Squill: Testing DBMS with Correctness Feedback and Accurate Instantiation." Applied Sciences 13, no. 4 (2023): 2519. http://dx.doi.org/10.3390/app13042519.

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Database Management Systems (DBMSs) are the core of management information systems. Thus, detecting security bugs or vulnerabilities of DBMSs is an essential task. In recent years, grey-box fuzzing has been adopted to detect DBMS bugs for its high effectiveness. However, the seed scheduling strategy of existing fuzzing techniques does not consider the seeds’ correctness, which is inefficient in finding vulnerabilities in DBMSs. Moreover, current tools cannot correctly generate SQL statements with nested structures, which limits their effectiveness. This paper proposes a fuzzing solution named

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Falcão, Fúlvio, João Moura, Gabriel Silva, Carlos Araujo, Erica Sousa, and Eduardo Tavares. "Energy Consumption and Performance Evaluation of Multi-Model NoSQL DBMSs." Revista de Informática Teórica e Aplicada 30, no. 2 (2024): 132–40. https://doi.org/10.22456/2175-2745.136568.

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New applications have required data storage using multiple data models, which are usually known as polyglot persistence applications. Their implementation is often complex, as the system must simultaneously manage and store data in multiple database management systems (DBMS). Over the years, multi-model DBMSs have been conceived, which commonly integrate multiple NoSQL data models into a single system. To demonstrate their feasibility, some researches have evaluated multi-model NoSQL DBMSs in the context of performance, but energy consumption is usually not taken into account. Indeed, energy c

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Butrovich, Matthew, Samuel Arch, Wan Shen Lim, William Zhang, Jignesh M. Patel, and Andrew Pavlo. "BPF-DB: A Kernel-Embedded Transactional Database Management System For eBPF Applications." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–27. https://doi.org/10.1145/3725272.

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Developers rely on the eBPF framework to augment operating system (OS) behavior for the betterment of database management system (DBMS) without having to modify kernel code. But eBPF's verifier limits program complexity and data management functionality. As a result eBPF's storage options are limited to kernel-resident, non-durable data structures that lack transactional guarantees. Inspired by embedded DBMSs for user-space applications, this paper present BPF-DB, an OS-embedded DBMS that offers transactional data management for eBPF applications. We explore the storage management and concurre

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Kakkar, Gaurav Tarlok, Jiashen Cao, Aubhro Sengupta, Joy Arulraj, and Hyesoon Kim. "Aero: Adaptive Query Processing of ML Queries." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–27. https://doi.org/10.1145/3725408.

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Query optimization is critical in relational database management systems (DBMSs) for ensuring efficient query processing. The query optimizer relies on precise selectivity and cost estimates to generate optimal query plans for execution. However, this static query optimization approach falls short for DBMSs handling machine learning (ML) queries. ML-centric DBMSs face distinct challenges in query optimization. First, performance bottlenecks shift to user-defined functions (UDFs), often encapsulating deep learning models, making it difficult to estimate UDF statistics without profiling the quer

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Stonebraker, Michael, and Andrew Pavlo. "What Goes Around Comes Around... And Around..." ACM SIGMOD Record 53, no. 2 (2024): 21–37. http://dx.doi.org/10.1145/3685980.3685984.

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Two decades ago, one of us co-authored a paper commenting on the previous 40 years of data modelling research and development [188]. That paper demonstrated that the relational model (RM) and SQL are the prevailing choice for database management systems (DBMSs), despite efforts to replace either them. Instead, SQL absorbed the best ideas from these alternative approaches. We revisit this issue and argue that this same evolution has continued since 2005. Once again there have been repeated efforts to replace either SQL or the RM. But the RM continues to be the dominant data model and SQL has be

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Győrödi, Cornelia A., Diana V. Dumşe-Burescu, Doina R. Zmaranda, Robert Ş. Győrödi, Gianina A. Gabor, and George D. Pecherle. "Performance Analysis of NoSQL and Relational Databases with CouchDB and MySQL for Application’s Data Storage." Applied Sciences 10, no. 23 (2020): 8524. http://dx.doi.org/10.3390/app10238524.

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In the current context of emerging several types of database systems (relational and non-relational), choosing the type and database system for storing large amounts of data in today’s big data applications has become an important challenge. In this paper, we aimed to provide a comparative evaluation of two popular open-source database management systems (DBMSs): MySQL as a relational DBMS and, more recently, as a non-relational DBMS, and CouchDB as a non-relational DBMS. This comparison was based on performance evaluation of CRUD (CREATE, READ, UPDATE, DELETE) operations for different amounts

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Yang, Rui, Ziyu Cui, Wensheng Dou, et al. "Detecting Isolation Anomalies in Relational DBMSs." Proceedings of the ACM on Software Engineering 2, ISSTA (2025): 1725–47. https://doi.org/10.1145/3728953.

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Relational Database Management Systems (DBMSs) utilize transactions to ensure data consistency and integrity, while providing multiple isolation levels to strike a balance between consistency and performance. However, isolation anomalies in relational DBMSs can undermine their claimed isolation levels, and lead to severe consequences, e.g., incorrect query results and database states. Existing isolation checkers can only work on simple key - value -like data models and the associated read ( key ) and write ( key , value ) operations. Therefore, they cannot be directly applied to relational DBM

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Lin, Li, Qinglin Zhu, Hongqiao Chen, Zhuangda Wang, Rongxin Wu, and Xiaoheng Xie. "QTRAN: Extending Metamorphic-Oracle Based Logical Bug Detection Techniques for Multiple-DBMS Dialect Support." Proceedings of the ACM on Software Engineering 2, ISSTA (2025): 731–52. https://doi.org/10.1145/3728908.

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Metamorphic testing is a widely used method to detect logical bugs in Database Management Systems (DBMSs), referred to herein as MOLT (Metamorphic-Oracle based Logical Bug Detection Technique). This technique involves constructing SQL statement pairs, including original and mutated queries, and assessing whether the execution results conform to predefined metamorphic relations to detect logical bugs. However, current MOLTs rely heavily on specific DBMS grammar to generate valid SQL statement pairs, which makes it challenging to adapt these techniques to various DBMSs with different grammatical

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Vishwakarma, Jaychand. "Transaction Processing Environment Kernelized Architecture in Multilevel Secure Application Policies." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 2 (2018): 87. http://dx.doi.org/10.23956/ijarcsse.v8i2.577.

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Multilevel security poses many challenging problems for transaction processing. The challenges are due to the conflicting requirements imposed by confidentiality, integrity, and availability} the three components of security. We identify these requirements on transaction processing in Multilevel Secure (MLS) database management systems (DBMSs) and survey the efforts of a number of researchers to meet these requirements .While our emphasis on centralized system based on kernelized Architecture, we briefly overview the research in the distributed MLS DBMSs as well.

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Tang, Xiu, Sai Wu, Dongxiang Zhang, Ziyue Wang, Gongsheng Yuan, and Gang Chen. "A Demonstration of DLBD: Database Logic Bug Detection System." Proceedings of the VLDB Endowment 16, no. 12 (2023): 3914–17. http://dx.doi.org/10.14778/3611540.3611584.

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Database management systems (DBMSs) are prone to logic bugs that can result in incorrect query results. Current debugging tools are limited to single table queries and struggle with issues like lack of ground-truth results and repetitive query space exploration. In this paper, we demonstrate DLBD, a system that automatically detects logic bugs in databases. DLBD offers holistic logic bug detection by providing automatic schema and query generation and ground-truth query result retrieval. Additionally, DLBD provides minimal test cases and root cause analysis for each bug to aid developers in re

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Mohr-Daurat, Hubert, Georgios Theodorakis, and Holger Pirk. "Hardware-Efficient Data Imputation through DBMS Extensibility." Proceedings of the VLDB Endowment 17, no. 11 (2024): 3497–510. http://dx.doi.org/10.14778/3681954.3682016.

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The separation of data and code/queries has served Data Management Systems (DBMSs) well for decades. However, while the resulting soundness and rigidity are the basis for many performance-oriented optimizations, it lacks the flexibility to efficiently support modern data science applications: data cleansing, data ingestion/augmentation or generative models. To support such applications without sacrificing performance, we propose a new logical data model called Homoiconic Collection Processing (HCP). HCP is based on a well-known Meta-Programming concept called Homoiconicity (a unified represent

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Cheung, Alvin, Maaz Bin Safeer Ahmad, Brandon Haynes, et al. "Towards Auto-Generated Data Systems." Proceedings of the VLDB Endowment 16, no. 12 (2023): 4116–29. http://dx.doi.org/10.14778/3611540.3611635.

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After decades of progress, database management systems (DBMSs) are now the backbones of many data applications that we interact with on a daily basis. Yet, with the emergence of new data types and hardware, building and optimizing new data systems remain as difficult as the heyday of relational databases. In this paper, we summarize our work towards automating the building and optimization of data systems. Drawing from our own experience, we further argue that any automation technique must address three aspects: user specification, code generation, and result validation. We conclude by discuss

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Patel, Dr Arjun S., and Prof Elena D. Petrovna. "CONVERGENT DATABASE ARCHITECTURES: MULTI-MODEL DESIGN AND QUERY OPTIMIZATION IN NEWSQL SYSTEMS." International Journal of Modern Computer Science and IT Innovations 2, no. 2 (2025): 10–18. https://doi.org/10.55640/ijmcsit-v02i02-02.

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The contemporary data landscape, characterized by diverse data types and escalating volumes, has driven a significant evolution in database management systems. Traditional Relational Database Management Systems (RDBMS) often struggle with the scalability and flexibility required for modern applications, while NoSQL databases, though scalable, frequently compromise on transactional consistency. NewSQL systems have emerged as a hybrid solution, aiming to combine the ACID guarantees of RDBMS with the horizontal scalability of NoSQL. This report explores the critical need for multi-model capabilit

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Terwilliger, James, Rafael Fernández-Moctezuma, Lois M. L. Delcambre, and David Maier. "Support for Schema Evolution in Data Stream Management Systems." JUCS - Journal of Universal Computer Science 16, no. (20) (2010): 3073–101. https://doi.org/10.3217/jucs-016-20-3073.

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Unlike Database Management Systems (DBMSs), Data Stream Management Systems (DSMSs) do not evaluate queries over static data sets — rather, they continuously produce result streams to standing queries, and often operate in a context where any interruption can lead to data loss. Support for schema evolution in such an environment is currently unaddressed. In this work we address evolution in DSMSs by introducing a new element to streams, called an accent, that precedes and describes an evolution. We characterize how a subset of commonly used query operators in DSMS act on and propagate accents w

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Arora, Pankaj, Surajit Chaudhuri, Sudipto Das, et al. "Flexible Resource Allocation for Relational Database-as-a-Service." Proceedings of the VLDB Endowment 16, no. 13 (2023): 4202–15. http://dx.doi.org/10.14778/3625054.3625058.

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Oversubscription is an essential cost management strategy for cloud database providers, and its importance is magnified by the emerging paradigm of serverless databases. In contrast to general purpose techniques used for oversubscription in hypervisors, operating systems and cluster managers, we develop techniques that leverage our understanding of how DBMSs use resources and how resource allocations impact database performance. Our techniques are designed to flexibly redistribute resources across database tenants at the node and cluster levels with low overhead. We have implemented our techni

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Wu, Zhiyong, Jie Liang, Jingzhou Fu, Mingzhe Wang, and Yu Jiang. "Hulk: Exploring Data-Sensitive Performance Anomalies in DBMSs via Data-Driven Analysis." Proceedings of the ACM on Software Engineering 2, ISSTA (2025): 2181–202. https://doi.org/10.1145/3728973.

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Performance is crucial for database management systems (DBMSs), and they are always designed to handle ever-changing workloads efficiently. However, the complexity of the cost-based optimizer (CBO) and its interactions can introduce implementation errors, leading to data-sensitive performance anomalies. These anomalies may cause significant performance degradation compared to the expected design under certain datasets. To diagnose performance issues, DBMS developers often rely on intuitions or compare execution times to a baseline DBMS. These approaches overlook the impact of datasets on perfo

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ElDahshan, Kamal A., AbdAllah A. AlHabshy, and Gaber E. Abutaleb. "Data in the time of COVID-19: a general methodology to select and secure a NoSQL DBMS for medical data." PeerJ Computer Science 6 (September 10, 2020): e297. http://dx.doi.org/10.7717/peerj-cs.297.

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Background As the COVID-19 crisis endures and the virus continues to spread globally, the need for collecting epidemiological data and patient information also grows exponentially. The race against the clock to find a cure and a vaccine to the disease means researchers require storage of increasingly large and diverse types of information; for doctors following patients, recording symptoms and reactions to treatments, the need for storage flexibility is only surpassed by the necessity of storage security. The volume, variety, and variability of COVID-19 patient data requires storage in NoSQL d

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Niketa Penumajji. "Transformations in Database and Data Processing Frameworks for Large-Scale Systems." international journal of engineering technology and management sciences 8, no. 5 (2024): 92–102. https://doi.org/10.46647/ijetms.2024.v08i05.013.

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With the exponential growth of data, traditional database management systems (DBMSs)face unprecedented challenges in scalability, performance, and flexibility. This paper surveys keydevelopments in scalable database systems, focusing on their evolution and integration with moderndistributed architectures such as MapReduce, HadoopDB, alongside systems like Presto, whichemphasize high-speed analytics through distributed SQL. We examine the role of parallelism, queryoptimization, and extensibility in enhancing system performance and resource efficiency. Byreviewing critical techniques, including

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Kuznetsov, Sergey Dmitrievich, Pavel Evgenievich Velikhov, and Qiang Fu. "Real-Time Analytics, Hybrid Transactional/Analytical Processing, In-Memory Data Management, and Non-Volatile Memory." Proceedings of the Institute for System Programming of the RAS 33, no. 3 (2021): 171–98. http://dx.doi.org/10.15514/ispras-2021-33(3)-13.

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These days, real-time analytics is one of the most often used notions in the world of databases. Broadly, this term means very fast analytics over very fresh data. Usually the term comes together with other popular terms, hybrid transactional/analytical processing (HTAP) and in-memory data processing. The reason is that the simplest way to provide fresh operational data for analysis is to combine in one system both transactional and analytical processing. The most effective way to provide fast transactional and analytical processing is to store an entire database in memory. So on the one hand,

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Kahn, M. G., L. M. Fagan, and S. Tu. "Extensions to the Time-Oriented Database Model to Support Temporal Reasoning in Medical Expert Systems." Methods of Information in Medicine 30, no. 01 (1991): 04–14. http://dx.doi.org/10.1055/s-0038-1634816.

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Physicians faced with diagnostic and therapeutic decisions must reason about clinical features that change over time. Database-management systems (DBMS) can increase access to patient data, but most systems are limited in their ability to store and retrieve complex temporal information. The Time-Oriented Databank (TOD) model, the most widely used data model for medical database systems, associates a single time stamp with each observation. The proper analysis of most clinical data requires accounting for multiple concurrent clinical events that may alter the interpretation of the raw data. Mos

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Klassen, R. K., and I. A. Kazantsev. "AUTOMATICAL PRETRANSLATION OF SQL-QUERIES TO A REGULAR PLAN IN CLUSTERIX-LIKE DBMS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 196 (October 2020): 11–20. http://dx.doi.org/10.14489/vkit.2020.10.pp.011-020.

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Previously completed designs for pretranslating SQL queries did not bring significant success. Nevertheless, such a pretranslator is necessary for the possibility of using Clusterix-like database management systems (DBMSs) by a wide circle of specialists. The article proposes an original approach to pretranslating SQL queries without writing operations to the regular plan for Clusterix-like DBMSs. The possibility of implementing such a pretranslator is discussed. The concepts of a hard and a simple SQL query are given. The basis of the pretranslator is a library for parsing arbitrary grammars

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Klassen, R. K., and I. A. Kazantsev. "AUTOMATICAL PRETRANSLATION OF SQL-QUERIES TO A REGULAR PLAN IN CLUSTERIX-LIKE DBMS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 196 (October 2020): 11–20. http://dx.doi.org/10.14489/vkit.2020.10.pp.011-020.

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Previously completed designs for pretranslating SQL queries did not bring significant success. Nevertheless, such a pretranslator is necessary for the possibility of using Clusterix-like database management systems (DBMSs) by a wide circle of specialists. The article proposes an original approach to pretranslating SQL queries without writing operations to the regular plan for Clusterix-like DBMSs. The possibility of implementing such a pretranslator is discussed. The concepts of a hard and a simple SQL query are given. The basis of the pretranslator is a library for parsing arbitrary grammars

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Никольский, Д. Р., В. Ф. Барабанов, Н. И. Гребенникова, С. А. Коваленко, and А. М. Нужный. "ANALYSIS OF GRAPH DATABASE MANAGEMENT SYSTEMS." ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА 19, no. 6(-) (2023): 13–20. http://dx.doi.org/10.36622/vstu.2023.19.6.002.

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в современном информационном обществе обработка данных стала важным инструментом для принятия обоснованных решений и достижения успеха во многих областях деятельности. Для хранения данных используют разные виды систем управления базами данных (СУБД), каждая из которых обладает своими уникальными функциями, преимуществами и вариантами использования. Графовые СУБД предлагают большое количество инструментов и методов анализа и обработки данных. Был произведен обзор графовой СУБД Neo4j, мультимодальных СУБД Virtuoso и ArangoDB, с поддержкой графовой модели данных и графовой СУБД Memgraph. Каждая и

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Zhang, Xinyi, Zhuo Chang, Yang Li, et al. "Facilitating database tuning with hyper-parameter optimization." Proceedings of the VLDB Endowment 15, no. 9 (2022): 1808–21. http://dx.doi.org/10.14778/3538598.3538604.

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Recently, using automatic configuration tuning to improve the performance of modern database management systems (DBMSs) has attracted increasing interest from the database community. This is embodied with a number of systems featuring advanced tuning capabilities being developed. However, it remains a challenge to select the best solution for database configuration tuning, considering the large body of algorithm choices. In addition, beyond the applications on database systems, we could find more potential algorithms designed for configuration tuning. To this end, this paper provides a compreh

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Lu, Kuan, Zhihui Yang, Sai Wu, Ruichen Xia, Dongxiang Zhang, and Gang Chen. "Adda: Towards Efficient in-Database Feature Generation via LLM-based Agents." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–27. https://doi.org/10.1145/3725262.

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Integrating machine learning (ML) analytics into existing database management systems (DBMSs) not only eliminates the need for costly data transfers to external ML platforms but also ensures compliance with regulatory standards. While some DBMSs have integrated functionalities for training and applying ML models for analytics, these tasks still present challenges, particularly due to limited support for automatic feature engineering (AutoFE), which is crucial for optimizing ML model performance. In this paper, we introduce Adda, an agent-driven in-database feature generation tool designed to a

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Krasnikov, I. L., A. K. Babichenko, and D. V. Snurnykov. "GENERAL CHARACTERISTICS AND SELECTION OF A DATABASE MANAGEMENT SYSTEM IN DISTANCE LEARNING." Integrated Technologies and Energy Saving, no. 4 (December 14, 2023): 58–66. http://dx.doi.org/10.20998/2078-5364.2023.4.06.

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The relevance of studying the discipline "Databases" for students of computer and engineering specialties is determined and their special needs and emphasis in learning are shown. The definition of the data model stored in the database is given. The features of the relational data model are considered, the main advantage of which is simplicity and accessibility for the user to understand and the availability of a fairly simple and at the same time powerful mathematical apparatus of set theory and relational algebra. The main educational elements of studying databases based on the relatio

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TIMAKOV, A. A. "SCENARIO OF INFORMATION FLOW ANALYSIS IMPLEMENTATION IN PL/SQL PROGRAM UNITS WITH PLIF PLATFORM." Программирование, no. 4 (July 1, 2023): 39–57. http://dx.doi.org/10.31857/s0132347423040118.

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Formal proof of security measure effectiveness and computation security is vitally important for trust in critical information systems. It should be realized that formal security verification must be carried out at each infrastructural level (from the hardware level to the application level) in the process of system design. Currently, computation security analysis on the application level remains the major challenge as it requires complex labeling of computing environment elements. Traditionally, to solve this problem, information flow control (IFC) methods are employed. Unlike access control

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Zhang, William, Wan Shen Lim, Matthew Butrovich, and Andrew Pavlo. "The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions." Proceedings of the VLDB Endowment 17, no. 11 (2024): 3373–87. http://dx.doi.org/10.14778/3681954.3682007.

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Existing machine learning (ML) approaches to automatically optimize database management systems (DBMSs) only target a single configuration space at a time (e.g., knobs, query hints, indexes). Simultaneously tuning multiple configuration spaces is challenging due to the combined space's complexity. Previous tuning methods work around this by sequentially tuning individual spaces with a pool of tuners. However, these approaches struggle to coordinate their tuners and get stuck in local optima. This paper presents the Proto-X framework that holistically tunes multiple configuration spaces. The ke

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FERREIRA, RENATO, TAHSIN KURC, MICHAEL BEYNON, CHIALIN CHANG, ALAN SUSSMAN, and JOEL SALTZ. "OBJECT-RELATIONAL QUERIES INTO MULTIDIMENSIONAL DATABASES WITH THE ACTIVE DATA REPOSITORY." Parallel Processing Letters 09, no. 02 (1999): 173–95. http://dx.doi.org/10.1142/s0129626499000190.

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As computational power and storage capacity increase, processing and analyzing large volumes of multi-dimensional datasets play an increasingly important role in many domains of scientific research. Scientific applications that make use of very large scientific datasets have several important characteristics: datasets consist of complex data and are usually multi-dimensional; applications usually retrieve a subset of all the data available in the dataset; various application-specific operations are performed on the data items retrieved. Such applications can be supported by object-relational d

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Matanat Hasanguliyeva, Asif Guluyev, Matanat Hasanguliyeva, Asif Guluyev. "DATABASE MANAGEMENT SYSTEMS SECURITY: RECENT THREATS AND PREVENTION METHODS." ETM - Equipment, Technologies, Materials 25, no. 01 (2024): 41–48. https://doi.org/10.36962/etm25012025-41.

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The core functionality of a Database Management System (DBMS) is to store and secure critical personal and corporate data. Number of web based applications using databases accessed through internet are increasing day by day. Preventing this environment and applications most of the time is not enough and possible, the counter measures, security threats and breaches are increasingly faced in general. In addition to the technical prevention methods, human factors and user awareness from beginners to experts must be taken into account. Extra effort should be spent to raise user awareness to a desi

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Markevich, D. V., V. V. Kharlanova, and A. D. Khomonenko. "INTEGRATION OF BUSINESS INTELLIGENCE SYSTEMS WITH DATABASE MANAGEMENT SYSTEMS IN TRANSPORT." H&ES Research 15, no. 2 (2023): 41–48. http://dx.doi.org/10.36724/2409-5419-2023-15-2-41-48.

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At present, the solution of various transport problems using information technologies is of great practical interest. To work with databases containing huge amounts of information, their structuring, thorough analysis and making optimal decisions, researchers and analysts actively use various systems, such as database management systems (DBMS) or business intelligence systems. Despite this, the integration of such systems, which can improve the quality of decisions, is still not widely used. Purpose: is to develop the integration technology between the business intelligence system and the DBMS

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Anjard, Ronald P. "The Basics of Database Management Systems (DBMS)." Industrial Management & Data Systems 94, no. 5 (1994): 11–15. http://dx.doi.org/10.1108/02635579410063261.

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Nguyen, Lam-Duy, Adnan Alhomssi, Tobias Ziegler, and Viktor Leis. "Moving on From Group Commit: Autonomous Commit Enables High Throughput and Low Latency on NVMe SSDs." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–24. https://doi.org/10.1145/3725328.

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Achieving both high throughput and low commit latency has long been a difficult challenge for Database Management Systems (DBMSs). As we show in this paper, existing commit processing protocols fail to fully leverage modern NVMe SSDs to deliver both high throughput and low-latency durable commits. We therefore propose autonomous commit , the first commit protocol that fully utilizes modern NVMe SSDs to achieve both objectives. Our approach exploits the high parallelism and low write latency of SSDs, enabling workers to explicitly write logs in smaller batches, thereby minimizing the impact of

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Celesti, Antonio, Maria Fazio, and Massimo Villari. "A Study on Join Operations in MongoDB Preserving Collections Data Models for Future Internet Applications." Future Internet 11, no. 4 (2019): 83. http://dx.doi.org/10.3390/fi11040083.

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Presently, we are observing an explosion of data that need to be stored and processed over the Internet, and characterized by large volume, velocity and variety. For this reason, software developers have begun to look at NoSQL solutions for data storage. However, operations that are trivial in traditional Relational DataBase Management Systems (DBMSs) can become very complex in NoSQL DBMSs. This is the case of the join operation to establish a connection between two or more DB structures, whose construct is not explicitly available in many NoSQL databases. As a consequence, the data model has

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