But in all seriousness, DataFrame centric operations are a superset of SQL (you can always do a df.sql("...") if you want to ) and have a lot more efficient implementation of both OLTP/ORM requirements and OLAP/DS/BI requirements.
They also encourage composability, modularization, reuse, unit and data testing ...
So it's ironic I feel like SQL's replacement is another declarative language - its original inspiration - plain English.
Just a natural language transpiler (like Palantir's Ontology plus Looker's Malloy (reverse disclaimer: I do not work for or enjoy either of these products but these underlying concepts are correct)) with some fancy domain heuristics and light AI (I suspect a Pareto like model that supports 80% of use cases only needs a semantic graph with a few thousand nodes and vertices)
But in all seriousness, DataFrame centric operations are a superset of SQL (you can always do a df.sql("...") if you want to ) and have a lot more efficient implementation of both OLTP/ORM requirements and OLAP/DS/BI requirements.
They also encourage composability, modularization, reuse, unit and data testing ...
So it's ironic I feel like SQL's replacement is another declarative language - its original inspiration - plain English.
Just a natural language transpiler (like Palantir's Ontology plus Looker's Malloy (reverse disclaimer: I do not work for or enjoy either of these products but these underlying concepts are correct)) with some fancy domain heuristics and light AI (I suspect a Pareto like model that supports 80% of use cases only needs a semantic graph with a few thousand nodes and vertices)