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I don't agree with the vilification of NoSQL, but I do agree that SQL is a great query language.

That's partly why I wanted to create a tool to query various databases (NoSQL ones or files too) with SQL. We're still in an early stage with OctoSQL regarding the variety of databases, but take a look if that sound appreciable to you: https://github.com/cube2222/octosql/

What sets OctoSQL apart from the existing options such as Apache Drill (even Spark SQL for that matter) or future projects such as PartiQL?

https://partiql.org/ https://drill.apache.org/

We're aiming to have very ergonomic stateful stream processing with only SQL and we're working on it currently. That's basically what's meant to set us apart.

So tapping into the change-logs of the underlying data-sources and providing a stream processing layer that's expressible in a stream SQL dialect?

btw, not being critical of your project, just trying to understand it.

Mainly thinking of explicitly stream oriented data sources like kafka, but yeah, change logs are really solved with an analogous abstraction.

There's a great paper on that: "One SQL to Rule Them All", check it out.

We also want to scale well from single computer one-of data exploration queries, to full blown clustered long-term stateful stream processing.

The point is to provide a well thought out SQL interface to as many data sources as possible, and like drill does, push down as much computation as possible.

We actually learned about drill only after creating OctoSQL, but that's another story. (We're definitely less mature currently and support fewer datasources)

Ha! I was going to link that to you once I understood what you meant.


I believe there is a similar effort going on in the Flink project. They're slowly merging in work from the Blink project to provide a unified SQL paradigm (batch + stream).

Yup, Akidaus book is a great resource too.

We're basically aiming for a middle ground between Flink, Presto and Drill.

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