![XLDB Analytics in on-line advertising OVERVIEW A comparison of several analytical methodologies was conducted by performing a standard on-line advertising campaign and audience analysis consisting of 67 queries against a 2 billion+ impression log file with 350 million unique “user-ids”. Methodologies included in the study: ,[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recomendados
Recomendados
Más contenido relacionado
La actualidad más candente
La actualidad más candente (20)
Destacado
Similar a Qo comparision
Similar a Qo comparision (20)
Último
Último (20)
Qo comparision
- 1. eXtremely large database (XLDB) analytics
- 4. Relational database, row oriented: MySQL, Oracle
- 5. Relational database, column oriented: Vertica
- 6. Hardware approach (brute force computing)
- 8. Distributed relational database: Aster Data
- 11. iQO can readily scale to petabyte volume applications whereas hadoop and Aster would reach unwieldy hardware proportions making them impractical to implement with extremely slow response times
- 12. MySQL and Oracle are not scalable for daily terabyte volumes
- 14. iQO Solutions Scalable & portable Uniquely suited for high volume and high cardinality Most queries returned in seconds Allows for Distinct Counts and Exclusive Counts not available in other solutions Lowest carbon footprint per query
- 16. Custom coding from skilled programmers required for each query
- 17. Inefficient data storage and management
- 18. Distinct counts difficult to achieve
- 19. Requires a team to manage effectively
- 20. No connectivity with BI and data mining tools
- 21. Business Objects
- 24. Distinct Counts difficult to achieve and Exclusive Counts not possible.
- 26. Space and server requirements to difficult to estimate
- 27. Query times would be impossibly long