Out of curiosity, are you planning on copying the data you store in HBase/Hive into separate Hadoop cluster in a different data center or backing up HDFS in some other manner? Redundancy isn't an issue within the cluster; it's more a concern of storing all your HDFS data in one physical location.
On Sun, Apr 25, 2010 at 8:04 AM, Joe Stump <j...@joestump.net> wrote: > > On Apr 25, 2010, at 11:40 AM, Mark Robson wrote: > > > For me an important difference is that Cassandra is operationally much > more straightforward - there is only one type of node, and it is fully > redundant (depending what consistency level you're using). > > > > This seems to be an advantage in Cassandra vs most other distributed > storage systems, which almost all seem to require some "master" nodes which > have different operational requirements (e.g. cannot fail, need to be failed > over manually or have another HA solution installed for them) > > These two remain the #1 and #2 reasons I recommend Cassandra over HBase. At > the end of the day, Cassandra is an *absolute* dream to manage across > multiple data centers. I could go on and on about the voodoo that is > expanding, contracting, and rebalancing a Cassandra cluster. It's pretty > awesome. > > That being said, we're getting ready to spin up an HBase cluster. If you're > wanting increment/decrement, more complex range scans, etc. then HBase is a > great candidate. Especially if you don't need it to span multiple data > centers. We're using Cassandra for our main things, and then HBase+Hive for > analytics. > > There's room for both. Especially if you're using Hadoop with Cassandra. > > --Joe > >
