That reminds me of a dream:

1. Write queries in datalog

2. Compose them like reusable functions

3. Stream that data between SQL db and dataframe columns and graph db

4. Both also supported with reusable composable function interfaces

5. With IDE/notebook feedback and content-assist including not just syntax but the referenced data model.

6. With distinct modes for exploring datasets and for generating code and tests for hardened pipelines.

7. With abstract accounting for operations of the db, transforms, and transfers.

Data and language will always have ultra-specialized forms. I’m looking for a low-overhead way to explore solutions using different combinations of baseline paradigms before generating code for the one to productize.