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Relational versus non-relational database systems for data warehousing

Published: 30 October 2010 Publication History

Abstract

Relational database systems have been the dominating technology to manage and analyze large data warehouses. Moreover, the ER model, the standard in database design has a close relationship with the relational model. Recently, there has been a surge of alternative technologies for large scale analytic processing, most of which are not based on the relational model. Out of these proposals, distributed file systems together with MapReduce have become strong competitors to relational database systems to analyze large data sets, exploiting parallel processing. Moreover, there is progress on using MapReduce to evaluate relational queries. With that motivation in mind, this panel will compare pros and cons of each technology for data warehousing and will identify research issues, considering practical aspects like ease of use, programming flexibility and cost; as well as technical aspects like data modeling, storage, hardware, scalability, query processing, fault tolerance and data mining.

References

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J. Dean and S. Ghemawat. MapReduce: a flexible data processing tool. Commun. ACM, 53(1):72--77, 2010.
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R. Elmasri and S. B. Navathe. Fundamentals of Database Systems. Addison/Wesley, 6th edition, 2010.
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C. Ordonez. Statistical model computation with UDFs. IEEE Transactions on Knowledge and Data Engineering (TKDE), 22, 2010.
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C. Ordonez and J. García-García. Database systems research on data mining. In Proc. ACM SIGMOD Conference, pages 1253--1254, 2010.
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M. Stonebraker, D. Abadi, D.J. DeWitt, S. Madden, E. Paulson, A. Pavlo, and A. Rasin. MapReduce and parallel DBMSs: friends or foes? Commun. ACM, 53(1):64--71, 2010.

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  • (2018)Improving the performance of Hadoop Hive by sharing scan and computation tasksJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-014-0012-63:1(1-11)Online publication date: 11-Dec-2018
  • (2017)Integrating the R Language Runtime System with a Data Stream WarehouseDatabase and Expert Systems Applications10.1007/978-3-319-64471-4_18(217-231)Online publication date: 2-Aug-2017
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Published In

cover image ACM Conferences
DOLAP '10: Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
October 2010
112 pages
ISBN:9781450303835
DOI:10.1145/1871940

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 October 2010

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Author Tags

  1. analysis
  2. data warehousing
  3. large databases

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  • Panel

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CIKM '10

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Overall Acceptance Rate 29 of 79 submissions, 37%

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Cited By

View all
  • (2018)A Survey on MapReduce ImplementationsInternational Journal of Cloud Applications and Computing10.4018/IJCAC.20160101046:1(59-87)Online publication date: 13-Dec-2018
  • (2018)Improving the performance of Hadoop Hive by sharing scan and computation tasksJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-014-0012-63:1(1-11)Online publication date: 11-Dec-2018
  • (2017)Integrating the R Language Runtime System with a Data Stream WarehouseDatabase and Expert Systems Applications10.1007/978-3-319-64471-4_18(217-231)Online publication date: 2-Aug-2017
  • (2017)An overview of online based platforms for sharing and analyzing electrophysiology data from big data perspectiveWIREs Data Mining and Knowledge Discovery10.1002/widm.12067:4Online publication date: 20-Apr-2017
  • (2016)Towards Performance Evaluation of Cloudant for Customer Representative Workloads2016 IEEE International Conference on Cloud Engineering Workshop (IC2EW)10.1109/IC2EW.2016.43(144-147)Online publication date: Apr-2016
  • (2015)Improving Hadoop Hive Query Response Times Through Efficient Virtual Resource AllocationFlexible Query Answering Systems 201510.1007/978-3-319-26154-6_17(215-225)Online publication date: 21-Oct-2015
  • (2013)A self-tuning system based on application Profiling and Performance Analysis for optimizing Hadoop MapReduce cluster configuration20th Annual International Conference on High Performance Computing10.1109/HiPC.2013.6799133(89-98)Online publication date: Dec-2013
  • (2013)An Economical Query Cost Model in the CloudProceedings of the 18th International Conference on Database Systems for Advanced Applications - Volume 782710.1007/978-3-642-40270-8_2(16-30)Online publication date: 22-Apr-2013
  • (2012)Parallel data processing with MapReduceACM SIGMOD Record10.1145/2094114.209411840:4(11-20)Online publication date: 11-Jan-2012
  • (2010)DOLAP 2010 workshop summaryProceedings of the 19th ACM international conference on Information and knowledge management10.1145/1871437.1871792(1973-1974)Online publication date: 26-Oct-2010

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