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Journal articles on the topic 'DBMS'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

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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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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Chen, Sibei, Ju Fan, Bin Wu, et al. "Automatic Database Configuration Debugging using Retrieval-Augmented Language Models." Proceedings of the ACM on Management of Data 3, no. 1 (2025): 1–27. https://doi.org/10.1145/3709663.

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Database management system (DBMS) configuration debugging, e.g., diagnosing poorly configured DBMS knobs and generating troubleshooting recommendations, is crucial in optimizing DBMS performance. However, the configuration debugging process is tedious and, sometimes challenging, even for seasoned database administrators (DBAs) with sufficient experience in DBMS configurations and good understandings of the DBMS internals (e.g., MySQL or Oracle). To address this difficulty, we propose Andromeda, a framework that utilizes large language models (LLMs) to enable automatic DBMS configuration debugg

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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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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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Van Aken, Dana, Dongsheng Yang, Sebastien Brillard, et al. "An inquiry into machine learning-based automatic configuration tuning services on real-world database management systems." Proceedings of the VLDB Endowment 14, no. 7 (2021): 1241–53. http://dx.doi.org/10.14778/3450980.3450992.

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Modern database management systems (DBMS) expose dozens of configurable knobs that control their runtime behavior. Setting these knobs correctly for an application's workload can improve the performance and efficiency of the DBMS. But because of their complexity, tuning a DBMS often requires considerable effort from experienced database administrators (DBAs). Recent work on automated tuning methods using machine learning (ML) have shown to achieve better performance compared with expert DBAs. These ML-based methods, however, were evaluated on synthetic workloads with limited tuning opportuniti

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Antonio, Ramon, and Rodriges Zalipynis. "SimDB in action." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3742–45. http://dx.doi.org/10.14778/3554821.3554889.

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Array DBMSs operate on big N -d arrays. Cellular automata (CA) work on a discrete lattice of cells, essentially on N -d arrays. CA facilitate decision support as they realistically simulate complex phenomena including road traffic, fire spread, and urban growth. Array DBMSs can bring numerous benefits to the CA domain via a "database approach": powerful parallelization, out-of-the box array operators, and interoperability to name a few. On the other hand, CA expand the area of Array DBMS applications and open a wide range of R&D opportunities. However, it is not straightforward to make an

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Zalipynis, Ramon Antonio Rodriges. "Array DBMS." Proceedings of the VLDB Endowment 14, no. 12 (2021): 3186–89. http://dx.doi.org/10.14778/3476311.3476404.

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Array DBMSs strive to be the best systems for managing, processing, and even visualizing big N -d arrays. The last decade blossomed with R&D in array DBMS, making it a young and fast-evolving area. We present the first comprehensive tutorial on array DBMS R&D. We start from past impactful results that are still relevant today, then we cover contemporary array DBMSs, array-oriented systems, and state-of-the-art research in array management, flavored with numerous promising R&D opportunities for future work. A great deal of our tutorial was not covered in any previous tutorial or sur

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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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Lerner, Alberto, Matthias Jasny, Theo Jepsen, Carsten Binnig, and Philippe Cudré-Mauroux. "DBMS annihilator." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3682–85. http://dx.doi.org/10.14778/3554821.3554874.

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Modern DBMS engines can achieve unprecedented transaction processing speeds thanks to the invention of clever data structures, concurrency schemes, and improvements in CPU and memory subsystems. However, developing realistic and efficient networked clients to benchmark these systems remains daunting. Simply put, traditional client-side networking stacks present high overheads and thus cannot exercise the high performance that modern DBMSs can, in principle, provide. In this demo, we propose a different approach to benchmarking; we showcase a new framework that leverages hardware-software co-de

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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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Lai, Yuanhao, Pengfei Zheng, Chenpeng Ji, et al. "Centrum: Model-based Database Auto-tuning with Minimal Distributional Assumptions." Proceedings of the ACM on Management of Data 3, no. 1 (2025): 1–26. https://doi.org/10.1145/3709671.

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Gaussian Process (GP)-based Bayesian optimization (BO), i.e., GP-BO, emerges as a prevailing model-based framework for DBMS (Database Management System) auto-tuning. However, recent work shows GP-BO-based DBMS auto-tuners are significantly outperformed by auto-tuners based on SMAC, which features random forest surrogate models; such results motivate us to rethink and investigate the limitations of GP-BO in auto-tuner design. We find that the fundamental assumptions of GP-BO are widely violated when modeling and optimizing DBMS performance, while tree-ensemble-BOs (e.g., SMAC) can avoid the ass

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Cereda, Stefano, Stefano Valladares, Paolo Cremonesi, and Stefano Doni. "CGPTuner." Proceedings of the VLDB Endowment 14, no. 8 (2021): 1401–13. http://dx.doi.org/10.14778/3457390.3457404.

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Properly selecting the configuration of a database management system (DBMS) is essential to increase performance and reduce costs. However, the task is astonishingly tricky due to a large number of tunable configuration parameters and their inter-dependencies. Also, the optimal configuration depends upon the workload to which the DBMS is exposed. To extract the full potential of a DBMS, we must also consider the entire IT stack on which the DBMS is running, comprising layers like the Java virtual machine, the operating system and the physical machine. Each layer offers a multitude of parameter

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Voronchikhin, M. V., and N. A. Galanina. "Using the Migration-KS Software Package to Solve the Problem of Database Import Substitution." Informacionnye Tehnologii 30, no. 9 (2024): 462–67. http://dx.doi.org/10.17587/it.30.462-467.

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Ways to solve the problem of import substitution and transfer of software to an open-source database management system (DBMS) in state and municipal institutions are considered (in particular, migration from a foreign SQL Server DBMS to domestic DBMSs based on PostgreSQL, such as PostgreSQL and DBMS-KS). The results of a detailed study of the main stages of database migration are presented, and the advantages and disadvantages of various migration methods are identified. A review of software solutions that enable the transition from MS SQL to PostgreSQL was carried out, such us AWS Database Mi

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Ghosh, Dhrubajyoti, Peeyush Gupta, Sharad Mehrotra, and Shantanu Sharma. "A Case for Enrichment in Data Management Systems." ACM SIGMOD Record 51, no. 2 (2022): 38–43. http://dx.doi.org/10.1145/3552490.3552497.

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We describe ENRICHDB, a new DBMS technology designed for emerging domains (e.g., sensor-driven smart spaces and social media analytics) that require incoming data to be enriched using expensive functions prior to its usage. To support online processing, today, such enrichment is performed outside of DBMSs, as a static data processing workflow prior to its ingestion into a DBMS. Such a strategy could result in a significant delay from the time when data arrives and when it is enriched and ingested into the DBMS, especially when the enrichment complexity is high. Also, enriching at ingestion cou

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Zalipynis, Ramon Antonio Rodriges, and Nikita Terlych. "WebArrayDB." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3622–25. http://dx.doi.org/10.14778/3554821.3554859.

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Geospatial array DBMSs operate on georeferenced N -d arrays. They provide storage engines, query parsers, and processing capabilities as their core functionality. Traditionally, those have been too heavy for a Web browser to support. Hence, Web Applications, mostly Geographic Information Systems (GISs), run array management on their server back-ends that return small portions of the results via the network. We showcase WebArrayDB, the first geospatial array DBMS that can run completely inside a Web browser. We demonstrate that modern Web browsers, JavaScript, and respective software libraries

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Zekri, Kaouther, Amel Grissa Touzi, and Noureddine Ellouze. "Optimized Image Retrieval System in Oracle DBMS." International Journal of Service Science, Management, Engineering, and Technology 8, no. 1 (2017): 1–17. http://dx.doi.org/10.4018/ijssmet.2017010101.

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In this work, the authors are moving towards the creation of an effective image retrieval system in Oracle DBMS. Several DBMSs have been extensively used to manage the textual information stored with images and CBIR tasks usually rely on specific applications. The separation between the DBMSs and CBIR prevents the optimization of integrated search process based on the connection between the textual and visual content description of image. Moreover, the relevance of image retrieval depends directly on the choice of similarity criteria (color, texture, shape) that can give inaccurate results in

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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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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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Liu, Chunwei, Anna Pavlenko, Matteo Interlandi, and Brandon Haynes. "A Deep Dive into Common Open Formats for Analytical DBMSs." Proceedings of the VLDB Endowment 16, no. 11 (2023): 3044–56. http://dx.doi.org/10.14778/3611479.3611507.

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This paper evaluates the suitability of Apache Arrow, Parquet, and ORC as formats for subsumption in an analytical DBMS. We systematically identify and explore the high-level features that are important to support efficient querying in modern OLAP DBMSs and evaluate the ability of each format to support these features. We find that each format has trade-offs that make it more or less suitable for use as a format in a DBMS and identify opportunities to more holistically co-design a unified in-memory and on-disk data representation. Our hope is that this study can be used as a guide for system d

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Sabbrina, Aura, Amanda oktavia Sufa, Dendi putra Ritonga, Efrida Rahma sari Siregar, and Nurbaiti . "Pengenalan Konsep Dasar Dan Penggunaan Database Manajemen Sistem (DBMS)." Jurnal Sains dan Teknologi (JSIT) 3, no. 3 (2023): 224–32. http://dx.doi.org/10.47233/jsit.v3i2.907.

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Penelitian ini bertujuan ini adalah untuk memperkenalkan konsep dasar database manajemen sistem yang dapat diterapkan sistem database manajemen pada setiap organisasi atau perusahaan maka perlu mengenal terlebih dahulu apa itu database manajemen sistem, bagaimana peranan database manajemen sistem, dan bagaimana struktur DBMS serta penerapan DBMS. Didalam dunia usaha, dunia pendidikan dan dunia kerja. Informasi adalah bagian penting sebagai informasi akurat dan tepat waktu akan membantu manajer dalam mengambil keputusan untuk mempertahankan dan mengembangkan organisasi dan usahanya. Maka dari i

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Zhang, Qizhen, Philip A. Bernstein, Badrish Chandramouli, Jiasheng Hu, and Yiming Zheng. "DDS: DPU-Optimized Disaggregated Storage." Proceedings of the VLDB Endowment 17, no. 11 (2024): 3304–17. http://dx.doi.org/10.14778/3681954.3682002.

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This paper presents DDS, a novel disaggregated storage architecture enabled by emerging networking hardware, namely DPUs (Data Processing Units). DPUs can optimize the latency and CPU consumption of disaggregated storage servers. However, utilizing DPUs for DBMSs requires careful design of the network and storage paths and the interface exposed to the DBMS. To fully benefit from DPUs, DDS heavily uses DMA, zero-copy, and userspace I/O to minimize overhead when improving throughput. It also introduces an offload engine that eliminates host CPUs by executing client requests directly on the DPU.

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Thüm, Thomas, Sandro Schulze, Mario Pukall, Gunter Saake, and Sebastian Günther. "Secure and Customizable Data Management for Automotive Systems: A Feasibility Study." ISRN Software Engineering 2012 (March 18, 2012): 1–7. http://dx.doi.org/10.5402/2012/424230.

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Custom tailor-made database management systems (DBMS) are an essential asset, especially for embedded systems. The continuously increasing amount of data in automotive systems and the growing network of embedded devices can profit from DBMS. Restrictions in terms of processors, memory, and storage require customizable DBMS that contain only the needed functionality. We present AutoDaMa, a customizable DBMS designed for automotive systems. With AutoDaMa, it is possible to generate tailor-made DBMS for different scenarios, for example, by restricting the storage size of the DBMS or adding securi

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Nurhanif, Nurhanif, Yuwaldi Away, and Muhammad Syukri Surbakti. "Performance Analysis of Database Synchronization on DBMS MySQL and Oracle by Using Event-Driven and Time-Driven Data for Monitoring Weather." Journal of Aceh Physics Society 10, no. 4 (2021): 107–12. http://dx.doi.org/10.24815/jacps.v10i4.20084.

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Abstrak. Data cuaca berupa suhu udara, kelembaban udara, curah hujan, dan kecepatan angin memerlukan proses penyimpanan yang baik supaya data cuaca dapat direkapitulasi selama satu tahun. Untuk itu membutuhkan proses penyimpanan data melalui Database Management System (DBMS). DBMS dapat mengelola, menyimpan sekumpulan data secara baik. Pengguna DBMS dapat membuat, mencari, memelihara, serta memiliki akses terkontrol terhadap data. Penyimpan data pada pemantauan cuaca menggunakan hardisk eksternal dalam format Comma Separated Values (CSV), penyimpanan data seperti ini kurang efisien diakibatkan

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Bansal, A. R., G. Gabriel, V. P. Dimri, and C. M. Krawczyk. "Estimation of depth to the bottom of magnetic sources by a modified centroid method for fractal distribution of sources: An application to aeromagnetic data in Germany." GEOPHYSICS 76, no. 3 (2011): L11—L22. http://dx.doi.org/10.1190/1.3560017.

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We propose a modified centroid method to compute the depth to the bottom of magnetic sources (DBMS) based on a fractal source distribution. This approach provides better estimates than the assumption of an uncorrelated source distribution. We apply our approach to a recently compiled homogeneous set of aeromagnetic data from Germany. The deepest DBMS values are found for some large basin areas, i.e., the Molasse basin and parts of the North German basin. Smaller DBMS were estimated for the Moldanubian region in southern Germany and the northern part of the North German basin. A comparison of D

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Zhang, Xinyi, Zhuo Chang, Hong Wu, et al. "A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning." Proceedings of the ACM on Management of Data 1, no. 2 (2023): 1–26. http://dx.doi.org/10.1145/3589331.

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Recently using machine learning (ML) based techniques to optimize the performance of modern database management systems (DBMSs) has attracted intensive interest from both industry and academia. With an objective to tune a specific component of a DBMS (e.g., index selection, knobs tuning), the ML-based tuning agents have shown to be able to find better configurations than experienced database administrators (DBAs). However, one critical yet challenging question remains unexplored -- how to make those ML-based tuning agents work collaboratively. Existing methods do not consider the dependencies

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Widodo. "Manajemen System (DBMS) Basic Concepts." Idaarotul Ulum (Jurnal Prodi MPI) 6, no. 01 (2024): 32–50. http://dx.doi.org/10.70688/idaarotululum.v6i01.386.

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Database Management System (DBMS) adalah sebuah perangkat lunak yang mendesain, mengelola, dan memanipulasi basis data. Konsep dasar DBMS meliputi pengorganisasian data, pemeliharaan integritas, dan penyediaan akses yang efisien ke informasi. DBMS mengizinkan pengguna untuk menyimpan, mengambil, dan memanipulasi data dengan cara yang terstruktur dan terpusat. Arsitektur DBMS mencakup komponen-komponen utama seperti model data, mesin penyimpanan, bahasa query, dan pengelola transaksi. Model data seperti model relasional, hierarkis, atau jaringan digunakan untuk mendefinisikan struktur data dala

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FONG, JOSEPH, and SHI-MING HUANG. "ARCHITECTURE OF A UNIVERSAL DATABASE: A FRAME MODEL APPROACH." International Journal of Cooperative Information Systems 08, no. 01 (1999): 47–82. http://dx.doi.org/10.1142/s0218843099000046.

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RDB has been dominant in the industry for the last decade. OODB is recongnized as a post-relational technology that can improve productivity, Hierarchical Database and Network Database were popular in the 1970s, and have been developed into legacy database systems. The DBMS of various data models have proliferated into many companies, and become their important assets. There is a need to integrate these database system into a data warehouse in the company. We investigate a solution to the problem by offering an architecture of a universal database for the connectivity of various DBMSs using di

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Putra, Yudha Yunanto, Oktania Purwaningrum, and Rivaldo Hadi Winata. "PERBANDINGAN PERFORMA RESPON WAKTU KUERI MYSQL, POSTGRESQL, DAN MONGODB." Jurnal Sistem Informasi dan Bisnis Cerdas 15, no. 1 (2022): 39–48. http://dx.doi.org/10.33005/sibc.v15i1.7.

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Teknologi telah mempengaruhi digitalisasi pada fungsi pekerjaan pada berbagai instansi. Pekerjaan dalam setiap fungsi kerja pada instansi dapat secara mudah dilakukan dengan adanya teknologi. Penggunaan teknologi berupa aplikasi membutuhkan sistem database untuk menyimpan data-data dan informasi pada suatu instansi. DBMS pada dasarnya terbagi menjadi 2 jenis yaitu DBMS relasional dan non-relasional. Contoh dari DBMS relasional adalah MySQL dan PostgreSQL, sedangkan DBMS non-relasional adalah MongoDB. Penelitian ini mengukur waktu yang diperlukan setiap DBMS dalam mengeksekusi query. Penelitian

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Currim, Sabah, Richard T. Snodgrass, Young-Kyoon Suh, and Rui Zhang. "DBMS Metrology." ACM Transactions on Database Systems 42, no. 1 (2017): 1–42. http://dx.doi.org/10.1145/2996454.

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Thompson, C. W., and P. Parkerson. "DBMS[me]." IEEE Internet Computing 8, no. 3 (2004): 85–89. http://dx.doi.org/10.1109/mic.2004.1297278.

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Ramakrishnan, Sub, and Emeka Nwosu. "DBMS course." ACM SIGCSE Bulletin 35, no. 1 (2003): 16–20. http://dx.doi.org/10.1145/792548.611922.

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Hallahan, Charles. "DBMS/COPY and DBMS/COPY Plus (Version 2.0)." American Statistician 46, no. 1 (1992): 49. http://dx.doi.org/10.2307/2684412.

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Hallahan, Charles. "DBMS/COPY and DBMS/COPY plus (Version 2.0)." American Statistician 46, no. 1 (1992): 49–52. http://dx.doi.org/10.1080/00031305.1992.10475849.

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Erdelt, Patrick K., and Jascha Jestel. "DBMS-Benchmarker: Benchmark and Evaluate DBMS in Python." Journal of Open Source Software 7, no. 79 (2022): 4628. http://dx.doi.org/10.21105/joss.04628.

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Hidayat, Wahyu, Muhammad Dwi Aldhi, and Dahliar Ananda. "Teknik Migrasi Data Lintas DBMS dengan Menggunakan Metadata." JURNAL INFOTEL - Informatika Telekomunikasi Elektronika 7, no. 2 (2015): 137. http://dx.doi.org/10.20895/infotel.v7i2.41.

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Proses migrasi data biasanya dibutuhkan saat adanya perubahan sistem, format, atau tipe storage. Saat ini telah dikenal beberapa teknik dan kakas untuk melakukan migrasi data, misalnya CSV file, ODBC, SQLDump dan sebagainya. Sayangnya tidak semua teknik tersebut dapat diimplementasikan untuk migrasi data antara dua DBMS yang berbeda. Dalam penelitian ini dipaparkan sebuah teknik migrasi data yang dapat digunakan untuk migrasi data lintas DBMS. Teknik migrasi data yang dipaparkan memanfaatkan metadata yang ada di masing-masing DBMS. Proses migrasi data yang dipaparkan di sini melalui tiga tahap

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Desai, Janvi. "Self-Optimizing Database Architecture." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (2021): 1675–78. http://dx.doi.org/10.22214/ijraset.2021.39071.

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Abstract: Over the most recent decades, analysts and database service providers have fabricated devices to help DBAs (Database Administrators) in various parts of framework tuning and the actual design of the database. Most of this past work, regardless, is fragmented on the grounds that it expects people to come up with an official agreement or judgement about any modifications to the data in the database and fix issues after they happen rather than preventing such cases from taking place or adjusting to these changes automatically. What is required for a really "self-driving" database manage

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RAKITSKIY, Yu S. "IMPORT AND EXPORT OF ROLE-BASED SECURITY POLICIES IN ORACLE DBMS." Mathematical structures and modeling, no. 4 (2018): 147–53. http://dx.doi.org/10.24147/2222-8772.2018.4.147-153.

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The article discusses the role-based security policy implemented in the Oracle DBMS. The role model in a DBMS can be quite complex, contain a large number of roles and authorities. This information is stored in a large number of related tables. A mechanism has been implemented to extract data mapped to role-based security policies in an Oracle DBMS and to present this information in GraphML format. It also implemented the ability to import role-based security policy, presented in GraphML format, in Oracle DBMS.

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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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Kawai, Yusuke, Jing Zhao, Kento Sugiura, Yoshiharu Ishikawa, and Yukiko Wakita. "An Analysis Technique of Evacuation Simulation Using an Array DBMS." Journal of Disaster Research 13, no. 2 (2018): 338–46. http://dx.doi.org/10.20965/jdr.2018.p0338.

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Today, large-scale simulations are thriving because of the increase of computating performance and storage capacity. Understanding the results of these simulations is not easy, and hence, support for interactive and exploratory analysis is becoming more important. This study focuses on spatio-temporal simulations and attempts to develop an analysis technology to support them. It uses a database system for supporting interactive analysis of large-scale data. Since the data gained via spatio-temporal simulations is not suitable for management in a relational DBMS (RDBMS), this study uses an arra

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Deshmukh, Om. "Data Migration Techniques across DBMS by Using Metadata." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (2022): 457–63. http://dx.doi.org/10.22214/ijraset.2022.47846.

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Abstract: The data migration process is usually needed when there is a change in system, format, or storage type. Currently, there are several techniques and tools for migrating data, for example, CSV files, ODBC, SQL Dump, and so on. Inappropriately not all of these techniques can be implemented for migrating data between two different DBMS. This research describes a data migration technique that can be used to migrate data across DBMS. The data migration technique described makes use of existing metadata in each DBMS. The data migration process described here goes through three stages, namel

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Annisa Rahmawita, Tania Azura Fahani, Rohima Rohima, Alwi Alviansha, and Nurbaiti Nurbaiti. "Implementasi Sistem Basis Data pada Sektor Pendidikan di Indonesia." INSOLOGI: Jurnal Sains dan Teknologi 2, no. 4 (2023): 684–89. http://dx.doi.org/10.55123/insologi.v2i4.2287.

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DBMS (Database Management System) is a software system that enables database users to maintain, control and access data in a practical and efficient manner. This DBMS is the layer that connects the database with application programs to ensure that the database remains consistently organized and can be accessed easily. The main purpose of using a DBMS in the education sector is to avoid confusion in terms of processing large amounts of data and to help students process data. DBMS also reduces and eliminates data redundancy and maximizes data consistency so that every time it displays data, the

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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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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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Jadhav, Priyanka, Pragati Patil, Nandini Chaudhari, and Sanmati Bedage. "Integrating Blended Active Teaching Learning Approach for DBMS Lab Course." Journal of Engineering Education Transformations 37, IS2 (2024): 469–76. http://dx.doi.org/10.16920/jeet/2024/v37is2/24076.

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Abstract— Data centralization, effective data management, and data access for application programs are all made simple by organizations by the database management system (DBMS) software. The role of DBMS is to provide an interface between physical data files and application programs. The use of the DBMS in the development of major applications and systems is essential. Currently, a number of big companies, nationally as well as globally, use databases as a backup for their application systems. Many highly well-known DBMS exist, including Oracle, Microsoft SQL Server, MySQL, PostgreSQL, Microso

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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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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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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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Sivov, V. V., and V. A. Bogatyrev. "Data Warehouse Failover Cluster for Analytical Queries in Banking." Advanced Engineering Research 23, no. 1 (2023): 76–84. http://dx.doi.org/10.23947/2687-1653-2023-23-1-76-84.

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Introduction. The banking sector assigns high priority to data storage, as it is a critical aspect of business operations. The volume of data in this area is steadily growing. With the increasing volume of data that needs to be stored, processed and analyzed, it is critically important to select a suitable data storage solution and develop the required architecture. The presented research is aimed at filling the gap in the existing knowledge of the data base management system (DBMS) suitable for the banking sector, as well as to suggest ways for a fault-tolerant data storage cluster. The purpo

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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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