September 14, 2015

DataStax and Cassandra update

MongoDB isn’t the only company I reached out to recently for an update. Another is DataStax. I chatted mainly with Patrick McFadin, somebody with whom I’ve had strong consulting relationships at a user and vendor both. But Rachel Pedreschi contributed the marvelous phrase “twinkling dashboard”.

It seems fair to say that in most cases:

Those generalities, in my opinion, make good technical sense. Even so, there are some edge cases or counterexamples, such as:

*And so a gas company is doing lightweight analysis on boiler temperatures, which it regards as hot data. :)

While most of the specifics are different, I’d say similar things about MongoDB, Cassandra, or any other NoSQL DBMS that comes to mind:

For DataStax Enterprise, exceptions start:

*As much as I love the “twinkling dashboard” term — it reminds me of my stock analyst days — it does raise some concerns. In many use cases, human real-time BI should be closely integrated with the more historical kind.

DataStax Enterprise:

This connects to what I said previously in that Cassandra 2.2 adds some analytic features, specifically in the area of user-defined functions. Notes on Cassandra 2.2 UDFs include:

And finally, some general tidbits:

Finally a couple of random notes:

Comments

6 Responses to “DataStax and Cassandra update”

  1. Mark Callaghan on September 14th, 2015 12:13 pm

    My guess is that the Apple workload on Cassandra is much more from iMessage than from iTunes.

  2. Curt Monash on September 14th, 2015 1:35 pm

    And MY guess is that I’m emphatically under NDA. :)

  3. Apple's secret NoSQL sauce includes a hefty dose of Cassandra | High Tech News on September 16th, 2015 10:23 am

    […] database guru Mark Callaghan posits that Apple’s Cassandra workload likely relates more to iMessage than iTunes, but whatever the […]

  4. Aaron on September 17th, 2015 9:26 am

    I’m not sure of Cassandra as the extreme write speed go to choice. It has good operational stability and has some nicer *read/search* capabilities than the KVPs of the world.

    High throughput writes tend to go to memcache or Redis (see a biased https://redislabs.com/cbc-2015-15-nosql-benchmark).

    Spark adds analytics (or even simple joins and other SQL niceties) and is typically run in parallel to a persistent store.

  5. Big Analytics Roundup (September 21, 2015) | The Big Analytics Blog on September 21st, 2015 1:17 pm

    […] a post about DataStax, Curt Monash notes synergies between Spark and […]

  6. Apple’s secret NoSQL sauce includes a hefty dose of Cassandra | nosqlblog on September 28th, 2015 4:58 pm

    […] database guru Mark Callaghan posits that Apple’s Cassandra workload likely relates more to iMessage than iTunes, but whatever the […]

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