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How does this compare to Splunk on machine data or Tableau on relational data?



Comparing to Tableau, Scuba is schema-less and doesn't require any setup beyond creating the table (which doesn't have any approval process in the way and gives you a reasonable amount of scratch space to test before you get serious) and then having data arrive. Once Scuba is aware of your column by you submitting data for it, it allows you to query/group based on it very quickly. Scuba is entirely real-time. There are some other projects to do pre-computed aggregates if that's important to you.

I haven't used Splunk in ~7 years, so I can't remember enough about it to compare well. Splunk has some structured-on-top-of-unstructured stuff in it, whereas Scuba is always structured. If you want to turn something unstructured into something structured, you generally run a separate pipeline to do that (using one of the tailing frameworks for your preferred language). In terms of the alarm system in Splunk, we have other systems for handling that using the data that flows into Scuba.


I don't know those platforms, but Scuba doesn't support relational operations. It's not as much of a limitation as it sounds like because you can log your data in a denormalized way.




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