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Actian Vector

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Vectorwise
Developer(s)Actian Corporation
Stable release
Vectorwise 2.0.2 / March 15, 2012 (2012-03-15)
Operating systemCross-platform
TypeRDBMS
LicenseProprietary
Websitewww.actian.com

Vectorwise is an SQL relational database management system designed for high performance in analytical database applications.[1] It currently holds the records as top performing database on the Transaction Processing Performance Council's TPC-H benchmark for database sizes of 100 GB, 300GB, and 1TB on non-clustered hardware. It has held these records since March 2011.[2][3][4]

Vectorwise originated as the X100 research project carried out within the Dutch National Research Institute for Mathematics and Computer Science (Centrum Wiskunde & Informatica (CWI)) between 2003 and 2008, and was released as a commercial product in June, 2010.[5][6][7] The current version was released on March 15, 2012, and is available for 64-bit Linux and Windows platforms.

Technology

The Vectorwise architecture makes use of "Vectorized Query Execution"— involving the principles of vector processing and Single Instruction, Multiple Data (SIMD)— to perform the same operation on multiple data simultaneously. This allows the database to reduce overheads found in traditional "tuple-at-a-time processing" and exploit data level parallelism on modern hardware, with fast transactional updates, a scan-optimised buffer manager and I/O, and a compressed NSM/DSM storage.[8]

History

A comparative TPC-H performance test of MonetDB carried out by its original creator at CWI in 2003 showed room for improvement in its performance as an analytical database. As a result, CWI researchers proposed a new architecture using pipelined query processing ("vectorised processing") to improve the performance of analytical queries. This led to the creation of the "X100" project, with the intention of designing a new kernel for MonetDB, to be called "MonetDB/X100".[9][10][11]

The X100 project team won the 2007 DaMoN Best Paper Award for the paper "Vectorized Data Processing on the Cell Broadband Engine"[12][13] as well as the 2008 DaMoN Best Paper Award for the paper "DSM vs. NSM: CPU Performance Tradeoffs in Block-Oriented Query Processing".[14][15]

In August 2009 the originators for the X100 project then won the "Ten Year Best Paper Award" at the 35th International Conference on Very Large Data Bases (VLDB) for their 1999 paper "Database architecture Optimized for the new bottleneck: Memory access". It was recognised by the VLDB that the project team had made great progress in implementing the ideas contained in the paper over the previous 10 years.[16] The central premise of the paper is that traditional relational database systems were designed in the late 1970s and early 1980s during a time when database performance was dictated by the time required to read from and write data to hard disk. At that time available CPU was relatively slow and main memory was relatively small, so that very little data could be loaded into memory at a time. The paper continues by suggesting that over time hardware has improved, with CPU speed and memory size doubling roughly every two years in accordance with Moore’s law, but that the design of traditional relational database systems has not adapted to reflect this. The CWI research team then goes on to describe improvements in database code and data structure to make best use of modern hardware, promoting "hardware aware" database design that exploits the potential of modern hardware.[17]

In 2008 the X100 project was spun off from MonetDB as a separate project in its own right, and renamed "VectorWise". In 2010, the VectorWise technology was acquired by Ingres Corporation.[6] Ingres Corporation later rebranded to Actian Corporation in 2011.[18]

See also


References

  1. ^ "Vectorwise Enterprise". Actian Corporation. Retrieved 3 May 2012.
  2. ^ "TPC-H - Top Ten Performance Results - Non-Clustered". Transaction Processing Performance Council. Retrieved 3 May 2012.
  3. ^ "Vectorwise Smashes TPC-H Record at Scale Factor 100 Delivering 340% of Previous Best Record" (Press release). Actian Corporation. 15 February 2011. Retrieved 3 May 2012.
  4. ^ "Vectorwise Breaks 300GB and 1TB TPC-H Benchmark Records Hands Down" (Press release). Actian Corporation. 4 May 2011. Retrieved 3 May 2012.
  5. ^ Clarke, Gavin (2 February 2010). "Ingres' VectorWise rises to answer Microsoft". The Register.
  6. ^ a b Babcock, Charles (9 June 2010). "Ingres Unveils VectorWise Database Engine". InformationWeek.
  7. ^ Suleman, Khidr (8 June 2010). "Ingres launches VectorWise database engine". V3. {{cite news}}: External link in |newspaper= (help)
  8. ^ Zukowski, Marcin; Boncz, Peter (March 2012). "Vectorwise: Beyond Column Stores" (PDF). IEEE Data Engineering Bulletin. 35 (1): 21–27. Retrieved 4 May 2012.
  9. ^ "Homepage of Peter Boncz". Retrieved 4 May 2012. {{cite web}}: Cite has empty unknown parameter: |name= (help)
  10. ^ "Faster database technology with MonetDB/X100". Centrum Wiskunde & Informatica. Retrieved 4 May 2012. {{cite web}}: Text "CWI Amsterdam" ignored (help); Text "Research in mathematics and computer science" ignored (help)
  11. ^ Marcin, Zukowski (11 September 2009). "Balancing vectorized query execution with bandwidth-optimized storage". Universiteit van Amsterdam. Retrieved 4 May 2012. {{cite journal}}: Cite journal requires |journal= (help)
  12. ^ "Vectorized Data Processing on the Cell Broadband Engine". Universiteit van Amsterdam. 2007. Retrieved 4 May 2012. {{cite journal}}: Cite journal requires |journal= (help)
  13. ^ "Third International Workshop on Data Management on New Hardware (DaMoN 2007)". Carnegie Mellon’s School of Computer Science (SCS). Retrieved 4 May 2012.
  14. ^ "DSM vs. NSM: CPU Performance Tradeoffs in Block-Oriented Query Processing". Universiteit van Amsterdam. 2008. Retrieved 4 May 2012. {{cite journal}}: Cite journal requires |journal= (help)
  15. ^ "Fourth International Workshop on Data Management on New Hardware (DaMoN 2008)". Carnegie Mellon’s School of Computer Science (SCS). Retrieved 4 May 2012.
  16. ^ "10-year Best Paper Award". International Conference on Very Large Data Bases. Retrieved 4 May 2012. {{cite web}}: Text "VLDB 2009" ignored (help)
  17. ^ "Database architecture optimized for the new bottleneck: Memory access". Universiteit van Amsterdam. 1999. Retrieved 4 May 2012. {{cite journal}}: Cite journal requires |journal= (help)
  18. ^ Clark, Don (22 September 2011). "Database-Software Firm Tries 'Action Apps'". The Wall Street Journal.
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