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Why Large Hadron Collider Scientists are Using CouchDB

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Re: Why Large Hadron Collider Scientists are Using CouchDB

#4

I hope they didn't upgrade to 1.0.0.

For the record I should note that CouchDB's durable storage format ensured that all the data affected by the 1.0.0 bug is recoverable. We think that in the end, because we announced the bug loudly and clearly, and provided a repair tool within days, no one lost any critical data.

Re: Why Large Hadron Collider Scientists are Using CouchDB

#5
I have no idea why they don't use something dynamo based like Riak or Cassandra which actually can automatically shard data and scale really well... CouchDB only supports replication, no sharding unless you use third party libraries. With Riak they could use the internal map/reduce support and with Cassandra they might be able to use Hadoop to analyze data and split the workload over several nodes.

Re: Why Large Hadron Collider Scientists are Using CouchDB

#6
post #5

I have no idea why they don't use something dynamo based like Riak or Cassandra which actually can automatically shard data and scale really well... CouchDB only supports replication, no sharding unless you use third party libraries. With Riak they could use the internal map/reduce support and with Cassandra they might be able to use Hadoop to analyze data and split the workload over several nodes.

If you read the case study you will see that building apps rapidly was a huge win for them. CouchDB gets compared with other DB's but it is a full stack app dev environment. The other NoSQL DB's need a Rails or PHP or Python or Java or C# or ... stack in front and app dev is nowhere as fast as with CouchApp.

Re: Why Large Hadron Collider Scientists are Using CouchDB

#8
post #5

I have no idea why they don't use something dynamo based like Riak or Cassandra which actually can automatically shard data and scale really well... CouchDB only supports replication, no sharding unless you use third party libraries. With Riak they could use the internal map/reduce support and with Cassandra they might be able to use Hadoop to analyze data and split the workload over several nodes.

They use it to store aggregated reports for distribution and analysis. It isn't doing any heavy lifting, and it's not a terribly compelling case study of anything.
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