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Comment by gigq | Hacker News Reader

This also exactly describes how HBase works. I've always preferred HBase to Cassandra for this exact reason. You put far less read load on your servers and you don't have to worry about most of the things on http://wiki.apache.org/cassandra/Operations.

Another benefit that is not mentioned is that with a master based system you can easily move who is responsible for the data if a server starts to hotspot. In Cassandra you have to use random key distribution because if you have a server hotspot then the only solution is to split the token ring which is an intensive operation that is hard to do while the server is under heavy load.

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Yep.

I hear the "master design is bad" argument all the time.

From many angles it is a bad design, but from other's it is not. First off, it is simpler and easier grok and check for bugs. Debugging a running system is easier.

It is also easier to implement different distribution strategies and failure/placementgroups, because that algorithms is centralized. If things go wrong it is easier to track where your data is.

No gossip rings to converge. And it is easier to grow the cluster.

/HBase committer here.

Thanks for the down vote.

If you find any technical inconsistencies in what I said, please let me know.

You could always just do a read=any on a cassandra cluster.

There are a few problems with read=any (or really read=one as any is only supported by writes). One issue is it will still send the request out to all the servers in the quorum so even if you don't have to wait on a quorum you still put the read load on them.

The second and more important issue is that if you want consistent data the only way to use read=one is if you use write=all which means you would have no resilience to a server outage. So in a normal cassandra cluster where you have write=quorum a read=one can give you back no data. In my experience this happened frequently enough with long GC pauses on one of the nodes that it wasn't useful to use in production.

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