New TPC benchmarks for decision support and web commerce
ACM SIGMOD Record
PrefixCube: prefix-sharing condensed data cube
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
SVL: Storage Virtualization Engine Leveraging DBMS Technology
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Performance tradeoffs in read-optimized databases
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
How to wring a table dry: entropy compression of relations and querying of compressed relations
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
XQueC: A query-conscious compressed XML database
ACM Transactions on Internet Technology (TOIT)
How to barter bits for chronons: compression and bandwidth trade offs for database scans
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
RadixZip: linear time compression of token streams
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Row-wise parallel predicate evaluation
Proceedings of the VLDB Endowment
An Alternative Data Warehouse Reference Architectural Configuration
BNCOD 26 Proceedings of the 26th British National Conference on Databases: Dataspace: The Final Frontier
The Use of the Binary-Relational Model in Industry: A Practical Approach
BNCOD 26 Proceedings of the 26th British National Conference on Databases: Dataspace: The Final Frontier
Efficient index compression in DB2 LUW
Proceedings of the VLDB Endowment
Using transparent compression to improve SSD-based I/O caches
Proceedings of the 5th European conference on Computer systems
Two-phase data warehouse optimized for data mining
BIRTE'06 Proceedings of the 1st international conference on Business intelligence for the real-time enterprises
Performance debugging of parallel compression on multicore machines
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part II
Database compression on graphics processors
Proceedings of the VLDB Endowment
Compression aware physical database design
Proceedings of the VLDB Endowment
Efficient compression of text attributes of data warehouse dimensions
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Transparent Online Storage Compression at the Block-Level
ACM Transactions on Storage (TOS)
Reordering rows for better compression: Beyond the lexicographic order
ACM Transactions on Database Systems (TODS)
FDB: a query engine for factorised relational databases
Proceedings of the VLDB Endowment
Evaluation of a Hybrid Approach for Efficient Provenance Storage
ACM Transactions on Storage (TOS)
Aggregation and ordering in factorised databases
Proceedings of the VLDB Endowment
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The Oracle RDBMS recently introduced an innovative compression technique for reducing the size of relational tables. By using a compression algorithm specifically designed for relational data, Oracle is able to compress data much more effectively than standard compression techniques. More significantly, unlike other compression techniques, Oracle incurs virtually no performance penalty for SQL queries accessing compressed tables. In fact, Oracle's compression may provide performance gains for queries accessing large amounts of data, as well as for certain data management operations like backup and recovery. Oracle's compression algorithm is particularly well-suited for data warehouses: environments, which contains large volumes of historical data, with heavy query workloads. Compression can enable a data warehouse to store several times more raw data without increasing the total disk storage or impacting query performance.