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Column Oriented Database Vs Row Oriented Databases

Column Oriented Database Vs Row Oriented Databases. By Rakesh Venkat. Index. Introduction- Column Oriented Databases List of Column Oriented Databases Pros and Cons MonetDB Performance Analysis LucidDB Performance Analysis Conclusion. Introduction.

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Column Oriented Database Vs Row Oriented Databases

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  1. Column Oriented Database VsRow Oriented Databases By Rakesh Venkat

  2. Index • Introduction- Column Oriented Databases • List of Column Oriented Databases • Pros and Cons • MonetDB • Performance Analysis • LucidDB • Performance Analysis • Conclusion

  3. Introduction • The Column Oriented Database stores data in columns . • It is mainly used in OLAP(online Analytical Processing), Data Mining oprerations.

  4. Pros • Data compression • Improved Bandwidth Utilization • Improved Code Pipelining • Improved cache locality

  5. Cons • Increased Disk Seek Time • Increased cost of Inserts • Increases tuple reconstruction costs

  6. List of Databases • Vertica • SybaseIQ • C-Store • BigTable • MonetDB • LucidDB

  7. MonetDB

  8. MonetDB(contd)

  9. MonetDB- Demo

  10. LucidDB • LucidDb tables are column store tables • Data in LucidDB is stored in Operating System in a file name as db.dat • Column store table consists of set of clusters. • Each column maps to single cluster. • A single cluster page, therefore, stores the values for a specific set of rowIDs for all columns in that cluster.

  11. Each cluster also has associated with it a btree index. • The btree index maps rid values to pageIds. • The rid values correspond to the first rid value stored on each page within a cluster, and the cluster pages are identified by their pageIds.

  12. LucidDB(contd)

  13. LucidDB(contd) • Within a cluster page, column values, by default, are stored in a compressed format, which allows LucidDB to minimize storage requirements. • The idea here is instead of storing each column value for every rid value on a page, we instead store just the unique column values. • We then associate with each column value a bit-encoded vector

  14. LucidDB • Demo

  15. Conclusion • Column architecture doesn’t read unnecessary columns • Avoids decompression costs and perform operations faster. • Use compression schemes allow us to lower our disk space requirements.

  16. References • Wikipedia, http://en.wikipedia.org/wiki/Column-oriented_DBMS Accessed – 14-sep-2007 • http://db.lcs.mit.edu/projects/cstore/abadisigmod06.pdf Accessed – 14-sep-2007 • http://marklogic.blogspot.com/2007/03/whats-column-oriented-dbms.html Accessed – 14-sep-2007 • http://en.wikipedia.org/wiki/MonetDB Accessed – 14-sep-2007 • http://monetdb.cwi.nl/projects/monetdb/SQL/QuickTour/index.html Accessed – 14-sep-2007 • Compression and Query Execution within Column Oriented Databases by Miguel C. Ferreira , MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 2005 • http://www.luciddb.org/ Accessed by 30-nov-2007.

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