ACM Transactions on Database Systems (TODS)
SIGMOD '85 Proceedings of the 1985 ACM SIGMOD international conference on Management of data
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Implementation techniques for main memory database systems
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Starburst Mid-Flight: As the Dust Clears
IEEE Transactions on Knowledge and Data Engineering
Weaving Relations for Cache Performance
Proceedings of the 27th International Conference on Very Large Data Bases
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
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
Breaking the memory wall in MonetDB
Communications of the ACM - Surviving the data deluge
Row-wise parallel predicate evaluation
Proceedings of the VLDB Endowment
Constant-Time Query Processing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
SIMD-scan: ultra fast in-memory table scan using on-chip vector processing units
Proceedings of the VLDB Endowment
Massively parallel sort-merge joins in main memory multi-core database systems
Proceedings of the VLDB Endowment
Enhancements to SQL server column stores
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
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DB2 with BLU Acceleration deeply integrates innovative new techniques for defining and processing column-organized tables that speed read-mostly Business Intelligence queries by 10 to 50 times and improve compression by 3 to 10 times, compared to traditional row-organized tables, without the complexity of defining indexes or materialized views on those tables. But DB2 BLU is much more than just a column store. Exploiting frequency-based dictionary compression and main-memory query processing technology from the Blink project at IBM Research - Almaden, DB2 BLU performs most SQL operations - predicate application (even range predicates and IN-lists), joins, and grouping - on the compressed values, which can be packed bit-aligned so densely that multiple values fit in a register and can be processed simultaneously via SIMD (single-instruction, multipledata) instructions. Designed and built from the ground up to exploit modern multi-core processors, DB2 BLU's hardware-conscious algorithms are carefully engineered to maximize parallelism by using novel data structures that need little latching, and to minimize data-cache and instruction-cache misses. Though DB2 BLU is optimized for in-memory processing, database size is not limited by the size of main memory. Fine-grained synopses, late materialization, and a new probabilistic buffer pool protocol for scans minimize disk I/Os, while aggressive prefetching reduces I/O stalls. Full integration with DB2 ensures that DB2 with BLU Acceleration benefits from the full functionality and robust utilities of a mature product, while still enjoying order-of-magnitude performance gains from revolutionary technology without even having to change the SQL, and can mix column-organized and row-organized tables in the same tablespace and even within the same query.