Mike Stonebraker

And so a stream processing engine looks nothing like a relational database.

And we had the gist of an idea for column stores for data warehouses, which was popularized by Vertica.

looks nothing like a row store.

So here were three wildly different implementations that had no resemblance to each other.

And in each case, they were an order of magnitude faster than the other guys.

So it's pretty clear that with those three instances, you give up an order of magnitude when you're running a database system that isn't

that isn't architected for your kind of stuff.

I think that's still true.

I mean, I think ClickHouse is a column store.

Pinecone is faster than user-defined types on text-based vector processing.

And so I think it's still very much the case.

And I think there's no difficulty putting a common parser on top of multiple implementations.

Postgres has so far chosen not to do that.

They don't implement a column store.

And so I think they are not competitive on sizable data warehouses.

They also don't have multi-node support, again, for people with big data warehouses.

That's table stakes.

So I think it's just as true today as it ever was.

I think that what is true is that if you want to get going, you have a database problem.

The answer is choose Postgres.