Splice Machine brings SQL Back, said Monte Zweben, CEO at Splice Machine, but with a spectacular twist.

It’s common for data infrastructure to reside on three separate platforms:  transactional databases, data warehouses, and the recently-added machine learning (ML) environment.

Most artificial intelligence (AI) applications are built on historical data that has been loaded in to ML environments for data mining.  So you’re looking in the rearview mirror to figure out what has already happened, he said.  And that requires computational engines.

Then, since you want to perform actions to make decisions in the moment, you need an operational data store, like traditional database management systems or a NoSQL data store, but people use these to make decisions in the application in the moment.

Lastly is new ML algorithms, data science workbenches and modeling workflows.