Why graph databases are becoming mainstream and their connection to AI, ML and big data use cases.

Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional ...

But Neptune also exemplifies another important development in graph databases: integration of data science and machine learning features.

That’s a learning curve.” Sahni feels that some applications should use a combination of relational and graph databases, with each type powering the individual functions that it does best.

If your database doesn’t already support internal machine learning, it’s likely that you can add that capability using MindsDB, which integrates with a half-dozen databases and five BI tools.