VLDB And BI

by Boris Evelson.

I’ve recently conducted research on the issues of VLDB (very large databases) and how it affects BI, since the challenges of reporting and analyzing Gb data sets are very different from reporting and analyzing multi Tb data sets. Among many other interesting findings and conclusions I uncovered the following approaches to handling VLDB challenges as they relate to BI:

Generic solutions by DBMS vendors:

  • Partitioning
  • Share everything vs. share nothing architecture
  • Caching, in-memory databases
  • Materialized views
  • Specialized file systems
  • Indexing (bit-map vs. B-tree)
  • Compression

BI-specific solutions by BI and other vendors:

  • DW appliances
  • ROLAP and reporting tool specific SQL optimization
  • Alternate DBMS (such as search indexes and vector DBMS)

I’d like to hear about other approaches that are used out there. Also, please join me for my upcoming teleconference on the subject: http://www.forrester.com/Teleconference/Overview/1,5158,1854,00.html