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What I meant was that, as far as I have seen, the tools that try to replace SQL by some OO intermediary, give you poorer abstractions that limit what you can do
by russell 18y ago
What I meant was that, as far as I have seen, the tools that try to replace SQL by some OO intermediary, give you poorer abstractions that limit what you can do. SQL seems clunky, but I think the core is quite well done considering when it comes from.
OTOH a relational relational database doesn't fit all needs. They scale pretty well, but when you get to gigantic data sets, they don't do so well and things like map reduce do a better job. Or cases where you are streaming massive amounts of data and you need performance, not ACID transaction reliability. Actually, we are more in agreement than disagreement.
- neilc 18y agoThey scale pretty well, but when you get to gigantic data sets, they don't do so well and things like map reduce do a better job. I don't think the evidence supports that. See the recent MR vs. parallel DB comparison, for example: http://database.cs.brown.edu/sigmod09/ http://database.cs.brown.edu/sigmod09/ There isn't a good massively parallel open source SQL implementation right now, but that is just a matter of engineering -- SQL databases have been shown to scale to massive data volumes (e.g. Fox Interactive have ~200 TB of user data in Greenplum, which is a parallel DB based on Postgres).