A Study of Modern Trends in Database and Data Repository Technologies as the Technological and Architectural Basis for the Creation of Software and Intelligent Systems by Means of Modern Programming Languages. Part 2

Keywords: databases, database management system, data warehouses, decision support systems, analytical data processing, structural query languange, data mining, transactional queries, analytic queries

Abstract

The article contains an analytical review of developments in database technologies, made on the basis of reports prepared by the results of eight meetings of database specialists held throughout 1988–2013. Objects of the analysis are most interesting predictions given in the reports: their realism, accuracy, pragmatism or, vice versa, utopianism or opportunism.   

The article consists of two parts.

Part 1 is devoted to analysis and evaluation of predictions made in the reports of the four earlier meetings held in 1988, 1990, 1995, and 1996. These predictions are about creation, development and uses of decision support systems, database appliances, graphic processing units, operating systems, interface for structured query language, database applications, information distribution, universal database management systems, query optimization criteria, intellectual analysis of database within database management systems. A detailed description of research themes in the field of databases, which got the priority status in that time, is given: recording and computation of data, security and confidentiality of data, replication and harmonization of data, structuring of data, intellectual analysis of data, data warehouses.   

Part 2 is devoted to an analytical review of the predictions contained in the reports on the meetings held in 1998, 2003, 2008, and 2013. The predictions are about self-adjustment of database systems, rethinking of the traditional database architecture as a result of new hardware capabilities. They make special emphasis on the feasibility of manipulations with structured and unstructured data within DSS architecture, support of Big Data technology, with outlining the themes of research aimed at implementation of its potential.     

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References

Kuznetsov S. D. (2010). MapReduce: vnutri, snaruzhi ili sboku ot parallelnyih SUBD? [MapReduce: within, outside, or on the side-by-side with parallel DBMSs?]. Trudy ISP RAN – Proceedings of the Institute for System Programing of the Russian Academy of Sciences, 19, 35–40 [in Russian].

Stonebraker M., Madden S., Abadi D. J., Harizopoulos S., Hachem N., & Helland P. (2007). The End of an Architectural Era (It’s Time for a Complete Rewrite). Proceedings of VLDB, 1150–1160.

Vertica Accelerator. The Fastest Analytics and Machine Learning – from Start to Finish. Retrieved from https://www.vertica.com/

VoltDB. Retrieved from https://www.voltdb.com/

Stonebraker M. & Çetintemel U. (2005). “One Size Fits All”: An Idea Whose Time Has Come and Gone. ICDE '05, Proceedings of the 21st International Conference on Data Engineering, 2–11.

Chaudhuri S., & Narasayya V. (1998). AutoAdmin “what-if” index analysis utility. SIGMOD '98, Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data, 367–378.

Bruno N., Chaudhuri S., Kӧnig A. C., Narasayya V., Ramamurthy R., & Syamala M. (2011). AutoAdmin Project at Microsoft Research: Lessons Learned. Bulletin of the Technical Committee on Data Engineering, vol. 34, issue 4, 12–19.

Belknap P., Beresniewicz J., Dageville B., Dias K., Shaft U., & Yagoub K. (2011). A Decade of Oracle Database Manageability. Bulletin of the Technical Committee on Data Engineering, vol. 34, issue 4, 20–27.

Kuznetsov S. D., & Prokhorov А. А. (2012). Algoritmyi upravleniya bufernyim pulom SUBD pri rabote s flesh-nakopitelyami [Algorithms for control of DBMS buffer pool in handling flash drives]. Trudy ISP RAN – Proceedings of the Institute for System Programing of the RAS, 23, 173–194. https://doi.org/10.15514/ISPRAS-2012-23-11 [in Russian].

Stonebraker M. (1987). The Design of the POSTGRES Storage System. VLDB '87, Proceedings of the 13th International Conference on Very Large Data Bases, 289–300.

DeBrabant J., Arulraj J., Pavlo A., Stonebraker M., Zdonik S. B., & Dulloor S. (2014). A Prolegomenon on OLTP Database Systems for Non-Volatile Memory. ADMS 2014, Fifth International Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures, 57–63.

Oukid I., & Lehner W. (2017). Towards a Single-Level Database Architecture on Non-Volatile Memory (Presentation Abstract). 8th Annual Non-Volatile Memories Workshop 2017, University of California.

Tumeo A., Secchi S., & Villa O. (2012). Designing Next-Generation Massively Multithreaded Architectures for Irregular Applications. Computer, vol. 45, issue 8, 53–61.

Schöning H. (2001). Tamino – A DBMS Designed for XML. ICDE '01, Proceedings of the 17th International Conference on Data Engineering, p. 149.

Fomichev A., Grinev M., & Kuznetsov S. (2006). Sedna: A Native XML DBMS. Lecture Notes in Computer Science, 3831, 272–281. https://doi.org/10.1007/11611257_25

Franklin M., Halevy A., & Maier D. (2005). From Databases to Dataspaces: A New Abstraction for Information Management. SIGMOD Record, vol. 34, issue 4, 27–33.

Virparia P. V., Buch S. H., & Parabia R. F. (2010). Trade and Tricks: Traditional vs. Virtual Data Warehouse. An International Journal of Advanced Engineering & Applications, 2010, vol. 2, issue 3, 225–239.

Inmon B. (2009). The Elusive Virtual Data Warehouse, March 19. Retrieved from https://www.academia.edu/562634/Trade_and_Tricks_Traditional_vs_Virtual_Data_Warehouse

Gadepally V., Chen P., Duggan J., Elmore A., Haynes B., Kepner J., et al. (2016). The BigDAWG Polystore System and Architecture. Proceedings of 2016 IEEE High Performance Extreme Computing Conference (HPEC), 1–6.

Pandis I., Johnson R., Hardavellas N., & Ailamaki A. (2010). Data-oriented transaction execution. Proceedings of the VLDB Endowment, vol. 3, issue 1, 928–939.

Kuznetsov S. D. (2017). Upravlenie dannyimi: 25 let prognozov [Data management: 25 years of forecasts]. Trudy ISP RAN – Proceedings of the Institute for System Programing of the Russian Academy of Sciences, 2017, 29(2), 117–160 [in Russian].


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Published
2022-06-01
How to Cite
YERSHOVA, O., & STAVYTSKYIО. (2022). A Study of Modern Trends in Database and Data Repository Technologies as the Technological and Architectural Basis for the Creation of Software and Intelligent Systems by Means of Modern Programming Languages. Part 2. Scientific Bulletin of the National Academy of Statistics, Accounting and Audit, (1-2), 76-85. https://doi.org/10.31767/nasoa.1-2-2022.09