Scalable Data Modelling by example – Cassandra Summit ’16

Two facts are the motivations for this talk:

  • First one is that the model cannot be changed once it is in production, well, you can, but by migrating data away to the new model using external tools such as Spark.
  • The second one is that one of the most common pain points in Cassandra deployments out there is actually performance issues caused by bad data models.

So in order to provide a Cassandra overview and a ‘checklist’ to follow when data modelling here you have my talk.

And the slides are here

Just as a final comment I’d like to remark that it was my bad that, during the talk, I forgot to acknowledge DataStax for all the amazing work they’re doing and because most of the content of this talk is taken from their Academy website. So once again, thanks DataStax for all your efforts, for such an amazing Summit and for all your contributions into the Cassandra Open Source project.

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