Vectorwise

From Wikipedia, the free encyclopedia
Jump to: navigation, search
Vectorwise
Developer(s) Actian Corporation
Stable release Vectorwise 2.5 / June 5, 2012 (2012-06-05)
Operating system Cross-platform
Type RDBMS
License Proprietary
Website www.actian.com

Vectorwise is an SQL relational database management system designed for high performance in analytical database applications.[1] It 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 held those records since March 2011.[2][3][4]

Vectorwise originated as the X100 research project carried out within the Centrum Wiskunde & Informatica (CWI, the Dutch National Research Institute for Mathematics and Computer Science) between 2003 and 2008, and was released as a commercial product in June, 2010.[5][6][7][8] A version released on 5 June 2012 was available for 64-bit Linux and Windows platforms.

Technology[edit]

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 colum-oriented as well as traditional relational model row-oriented storage.[9]

History[edit]

A comparative Transaction Processing Performance Council TPC-H performance test of MonetDB carried out by its original creator at Centrum Wiskunde & Informatica (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".[10][11][12]

The X100 project team won the 2007 DaMoN Best Paper Award for the paper "Vectorized Data Processing on the Cell Broadband Engine"[13][14] as well as the 2008 DaMoN Best Paper Award for the paper "DSM vs. NSM: CPU Performance Tradeoffs in Block-Oriented Query Processing".[15][16]

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.[17] 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. Over time hardware 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 had not adapted. The CWI research team described improvements in database code and data structures to make best use of modern hardware.[18]

In 2008 the X100 project was spun off from MonetDB as a separate project in its own right, and renamed "VectorWise". Co-founders included Peter A. Boncz and Marcin Zukowski.[19][20] In 2010, the VectorWise technology was announced by Ingres Corporation.[6] Ingres Corporation later rebranded to Actian Corporation in 2011.[21]

See also[edit]

References[edit]

  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.co.uk. 
  8. ^ Marcin Zukowski and Peter Boncz (20 May 2012). "From x100 to vectorwise: opportunities, challenges and things most researchers do not think about". Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (ACM): 861–862. doi:10.1145/2213836.2213967. ISBN 978-1-4503-1247-9. 
  9. ^ Zukowski, Marcin; Boncz, Peter (March 2012). "Vectorwise: Beyond Column Stores". IEEE Data Engineering Bulletin 35 (1): 21–27. Retrieved 4 May 2012. 
  10. ^ "Homepage of Peter Boncz". Retrieved 4 May 2012. 
  11. ^ "Faster database technology with MonetDB/X100". Centrum Wiskunde & Informatica. Retrieved 4 May 2012. 
  12. ^ Marcin, Zukowski (11 September 2009). Balancing vectorized query execution with bandwidth-optimized storage. Universiteit van Amsterdam. Retrieved 4 May 2012. 
  13. ^ Vectorized Data Processing on the Cell Broadband Engine. Universiteit van Amsterdam. 2007. Retrieved 4 May 2012. 
  14. ^ "Third International Workshop on Data Management on New Hardware (DaMoN 2007)". Carnegie Mellon’s School of Computer Science (SCS). Retrieved 4 May 2012. 
  15. ^ Zukowski, Marcin; Nes, Niels J.; Boncz, Peter A. (June 2008). "DSM vs. NSM: CPU Performance Tradeoffs in Block-Oriented Query Processing". Proceedings of the International Workshop on Data Management on New Hardware (Universiteit van Amsterdam). doi:10.1145/1457150.1457160. Retrieved 11 December 2013. 
  16. ^ "Fourth International Workshop on Data Management on New Hardware (DaMoN 2008)". Carnegie Mellon School of Computer Science. Retrieved 4 May 2012. 
  17. ^ "10-year Best Paper Award – VLDB 2009". International Conference on Very Large Data Bases. Retrieved 4 May 2012. 
  18. ^ Boncz, Peter; Manegold, Stefan; Kersten, Martin L. (15 June 1999). "Database architecture optimized for the new bottleneck: Memory access". Proceedings of the 25th International Conference on Very Large Data Bases (Universiteit van Amsterdam): 54–65. ISBN 1-55860-615-7. Retrieved 11 December 2013. 
  19. ^ Curt Monash (25 April 2013). "Goodbye VectorWise, farewell ParAccel?". DBMS2. Retrieved 11 December 2013. 
  20. ^ "Peter Boncz". Staff web page. CWI. Retrieved 11 December 2013. 
  21. ^ Clark, Don (22 September 2011). "Database-Software Firm Tries 'Action Apps'". The Wall Street Journal. 

External links[edit]