Cool article! Datalog is definitely worth more attention!
Just a detail: In fairness, I think one can say that there is actually one more "implementation" of datalog for Clojure, though it is built upon the Hadoop ecosystem, Cascalog [1].
I just hope they get Apache Spark support out of the door soon, as that would make it a lot more useful for things with any kind of requirements on delay.
But most of all, I wish there was a solid open source disk-based database/data system out there that did NOT need the overhead of a Hadoop, nor Spark installation. That would be killer!
It is a datalog like fragment without recursion but with added negation. Which makes it more like a pretty syntax for conjunctive queries with negation and thus equivalent in power to SQL.
The tree example of the article would thus not be possible in cascalog.
If anybody wonders, the no. 1 reason I find datalog so compelling, is the support for "named queries", which basically means that you can store a complex lookup as named "concept", which is then usable in other queries.
This, combined with the pattern-matching oriented syntax that leverages implicit JOINs, makes it so much more useful (it seems to me), than SQL VIEWs (which would be the SQL counterpart to datalog's named queries) will ever be (Correct me if I'm wrong!).
Just a detail: In fairness, I think one can say that there is actually one more "implementation" of datalog for Clojure, though it is built upon the Hadoop ecosystem, Cascalog [1].
I just hope they get Apache Spark support out of the door soon, as that would make it a lot more useful for things with any kind of requirements on delay.
But most of all, I wish there was a solid open source disk-based database/data system out there that did NOT need the overhead of a Hadoop, nor Spark installation. That would be killer!
[1] http://cascalog.org