April 30, 2014

Cloudera, Impala, data warehousing and Hive

There’s much confusion about Cloudera’s SQL plans and beliefs, and the company has mainly itself to blame. That said, here’s what I think is going on.

And of course, as vendors so often do, Cloudera generally overrates both the relative maturity of Impala and the relative importance of the use cases in which its offerings – Impala or otherwise – shine.

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4 Responses to “Cloudera, Impala, data warehousing and Hive”

  1. Mark Callaghan on April 30th, 2014 10:55 pm

    Does Impala do index nested loops joins with HBase?

  2. Kris Peeters on May 1st, 2014 2:54 am

    About impala performance, we ran our own comparison against Vertica: http://baboonit.be/blog/measuring-vertica-performance-with-tpc-ds

    For the results they published, impala is actually quite fast. They didn’t publish concurrency results.

  3. Marcel Kornacker on May 4th, 2014 9:57 pm

    Mark: Impala does not yet support index nested loop joins against HBase, but it’s something we’re looking at. No release date yet, though.

  4. John on May 19th, 2014 10:28 am

    There is another SQL implementation on HBASE by name of Splice Machine. They provide ACID compliance. After downloading the product on single node and trying for simple testing was completely disappointed by what splice machine has to offer. First, it is SQL on Hbase (not sure why does that make it a RDBMS) or SQL on Hadoop i.e. lots of marketing in their material.
    Secondly, product is using Derby for the front end SQL layer and most of the execution is extremely slow as lots of operations (like Joins) happen in the JVMs. SQL isn’t complete, you need an Oracle Expert from early 1980s to make Splice machine work. Query performance even on Single node on small dataset was below par. Transaction thru put doesn’t keep up with likes of VoltDB or NoSQL.
    Will be downloading Impala and give it a shot next.

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