Vertica Spells Out Compression ClaimsVertica Spells Out Compression Claims

Omer Trajman of column-store DBMS vendor Vertica put up a must-read blog spelling out detailed compression numbers, based on actual field experience (which I'd guess is from a combination of production systems and POCs):• CDR - 8:1 (87%) • Consumer Data - 30:1 (96%) • Marketing Analytics - 20:1 (95%) • Network logging - 60:1 (98%) • Switch Level SNMP - 20:1 (95%) • Trade and Quote Exchange - 5:1 (80%) • Trade Execution Auditing Trails - 10:1 (90%) • Weblog and Click-stream - 10:1 (90%)

It's clear what Omer means by most of those categories from reading the post, but I'm a little fuzzy on what "Consumer Data" or "Marketing Analytics" comprise in his taxonomy. Anyhow, Omer's post is a huge improvement over my recent one - based on a conversation with Omer - which featured far less accurate and complete compression numbers.

Omer goes on to claim that trickle-feed data is harder for rival systems to compress than it is for Vertica, and generally to claim that Vertica's compression is typically severalfold better than that of competitive row-based systems.Omer Trajman of column-store DBMS vendor Vertica put up a must-read blog spelling out detailed compression numbers, based on actual field experience... Omer goes on to claim that Vertica's compression is typically severalfold better than that of competitive row-based systems.