The server side compression can compress across columns/rows so it will most likely be more efficient.
Whether you are CPU bound or IO bound depends on your application and node setup. Unless your working set fits in memory you will be IO bound, and in that case server side compression helps because there is less to read from disk. In many cases it is actually
faster to read a compressed file from disk and decompress it, then to read an uncompressed file from disk.
See Ed's post:
"Cassandra compression is like more servers for free!"
From: email@example.com [firstname.lastname@example.org] on behalf of Ben McCann [email@example.com]
Sent: Monday, April 02, 2012 10:42 AM
Subject: Compression on client side vs server side
I was curious if I compress my data on the client side with Snappy whether there's any difference between doing that and doing it on the server side? The wiki said that compression works best where each row has the same columns. Does this mean the compression
will be more efficient on the server side since it can look at multiple rows at once instead of only the row being inserted? The reason I was thinking about possibly doing it client side was that it would save CPU on the datastore machine. However, does
this matter? Is CPU typically the bottleneck on a machine or is it some other resource? (of course this will vary for each person, but wondering if there's a rule of thumb. I'm making a web app, which hopefully will store about 5TB of data and have 10s of
millions of page views per month)