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I agree about Oracle's lack of a strategy that incorporates Hadoop is definitely going to hurt them. With the addition of Spark the Hadoop platform is looking like being the first choice for analysing data sets whether small or big. And whilst I am sure SQL has and will continue to be a major part of that it won't be the only approach. There will be R, PMML, Python, Scala and a whole lot more.

That aside Facebook having a buy versus build decision to make seems pretty strange. What would they even buy given that Cassandra and HBase which they created are two of the most scalable databases right now. Strange observation.




Oracle partners with Cloudera for their hadoop servers: https://www.oracle.com/engineered-systems/big-data-appliance...

Hadoop is not what the article is talking about though, nor is Cassandra. The issue is not about whether it scales out or not, it's about whether it is memory-based or disk-based. If queries have to pass through a block API at any point, they can never perform as well as a database where all queries run out of main memory, like Hana or VoltDB. On block-based systems you can't run some categories of analytical queries interactively, they always end up being too slow.

He's saying oracle has a problem because they don't have a good in-memory story ready. Right now they're aiming at this problem from two directions: Oracle NoSQL (a distributed KV store comparable to Riak), and Oracle 12c In-Memory (in-memory engine bolted onto the oracle db). Neither are particularly convincing to me, and definitely not a match for Hana or VoltDB.


I think your comment explains the problem clearly and should be at the top. To add more bluntness, Oracle's problem is that their typical enterprise customers who may be interested in, or require, in-memory databases have no practical option but to abandon Oracle. And if they move away from Oracle for analytics, what's stopping them from considering moving away for transactional work as the next step?




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