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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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loom
Graph library for Clojure. Mailing list https://groups.google.com/forum/#!forum/loom-clj (by aysylu)
That's essentially how we have it all working internally already, and the edn-based relational algebra IR looks something like: https://github.com/xtdb/core2/blob/dc8edd13995717675a6a2b8f6ee3f05a8dc05f5c/modules/datasets/src/core2/tpch.clj#L95 Note that we have the seeds of an edn-Datalog frontend implementation here: https://github.com/xtdb/core2/blob/master/test/core2/datalog/datalog_test.clj / https://github.com/xtdb/core2/blob/master/core/src/core2/datalog.clj (crucially though there is no rules / recursion support yet, so it's not yet a true Datalog!)
Yep, that's exactly the vision here. One of the biggest sources of precedent and inspiration for us here is https://partiql.org/ which is picking up a fair bit of traction across AWS. Also see https://rockset.com/
Datomic's original insight and value prop is code/data locality (the "how" is as you say – efficient distributed reads). Thereby interleaving the Datomic entity API with your dynamic application logic as if the entity graph was walkable like in-memory data structure, in contrast with big-join-up-front declarative/static query patterns you see in SQL that batch data access for efficiency. For example you could use aysylu/loom generic graph traversals against a datomic entity graph and the idea was that this would be efficient.