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The implementation and performance of compressed databases

Published: 01 September 2000 Publication History

Abstract

In this paper, we show how compression can be integrated into a relational database system. Specifically, we describe how the storage manager, the query execution engine, and the query optimizer of a database system can be extended to deal with compressed data. Our main result is that compression can significantly improve the response time of queries if very light-weight compression techniques are used. We will present such light-weight compression techniques and give the results of running the TPC-D benchmark on a so compressed database and a non-compressed database using the AODB database system, an experimental database system that was developed at the Universities of Mannheim and Passau. Our benchmark results demonstrate that compression indeed offers high performance gains (up to 50%) for IO-intensive queries and moderate gains for CPU-intensive queries. Compression can, however, also increase the running time of certain update operations. In all, we recommend to extend today's database systems with light-weight compression techniques and to make extensive use of this feature.

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  • (2024)ClickHouse - Lightning Fast Analytics for EveryoneProceedings of the VLDB Endowment10.14778/3685800.368580217:12(3731-3744)Online publication date: 1-Aug-2024
  • (2024)CStream: Parallel Data Stream Compression on Multicore Edge DevicesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.338686236:11(5889-5904)Online publication date: Nov-2024
  • (2024)Joint Directory, File and IO Trace Feature Extraction and Feature-based Trace Regeneration for Enterprise Storage Systems2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00307(4002-4015)Online publication date: 13-May-2024
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Information & Contributors

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Published In

cover image ACM SIGMOD Record
ACM SIGMOD Record  Volume 29, Issue 3
Sept. 2000
86 pages
ISSN:0163-5808
DOI:10.1145/362084
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2000
Published in SIGMOD Volume 29, Issue 3

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Cited By

View all
  • (2024)ClickHouse - Lightning Fast Analytics for EveryoneProceedings of the VLDB Endowment10.14778/3685800.368580217:12(3731-3744)Online publication date: 1-Aug-2024
  • (2024)CStream: Parallel Data Stream Compression on Multicore Edge DevicesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.338686236:11(5889-5904)Online publication date: Nov-2024
  • (2024)Joint Directory, File and IO Trace Feature Extraction and Feature-based Trace Regeneration for Enterprise Storage Systems2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00307(4002-4015)Online publication date: 13-May-2024
  • (2023)The FastLanes Compression Layout: Decoding > 100 Billion Integers per Second with Scalar CodeProceedings of the VLDB Endowment10.14778/3598581.359858716:9(2132-2144)Online publication date: 1-May-2023
  • (2023)High-Ratio Compression for Machine-Generated DataProceedings of the ACM on Management of Data10.1145/36267321:4(1-27)Online publication date: 12-Dec-2023
  • (2022)Toward Quantity-of-Interest Preserving Lossy Compression for Scientific DataProceedings of the VLDB Endowment10.14778/3574245.357425516:4(697-710)Online publication date: 1-Dec-2022
  • (2022)Robust and budget-constrained encoding configurations for in-memory database systemsProceedings of the VLDB Endowment10.14778/3503585.350358815:4(780-793)Online publication date: 14-Apr-2022
  • (2022)Accelerating database analytic query workloads using an associative processorProceedings of the 49th Annual International Symposium on Computer Architecture10.1145/3470496.3527435(623-637)Online publication date: 18-Jun-2022
  • (2022)A Method for Data Compression and Personal Information Suppressing in Columnar DatabasesEmerging Technologies in Computer Engineering: Cognitive Computing and Intelligent IoT10.1007/978-3-031-07012-9_46(543-559)Online publication date: 26-May-2022
  • (2021)Columnar storage and list-based processing for graph database management systemsProceedings of the VLDB Endowment10.14778/3476249.347629714:11(2491-2504)Online publication date: 27-Oct-2021
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