[adamneilson]

I think Datomic which has been doing time series data for years now answers the "what’s the big deal" question for me:

"Given a value of the database, one can obtain another value of the database as-of, or since, a point in time in the past, or both (creating a windowed view of activity). These database values can be queried ordinarily, without having to make special queries parameterized by time." http://www.datomic.com/rationale.html

So in other words you get to see exactly how the whole database looked at any given moment through history (certain parallels with the blockchain I suppose).

[zcam]

Until you reach 10B datoms and then you're off for a fun ride sharding with multiple databases. Also in an IoT context or more general timeseries usage you very likely don't care about tx, but very much do about write throughput and not having a spof, which Datomic isn't good at at all.

Datomic is an ok choice in some contexts, but the one detailed here is not one of them, you're likely to reach Datomic limits quickly and be in a world of hurt when you do.

[assface]

> I think Datomic which has been doing time series data for years now answers the "what’s the big deal" question for me:

This is known as "time travel queries". Postgres supported this back in the original version from the 1980s but then they took it out in 1997 because it takes up too much disk space.

It's trivial to do in an MVCC system. You just turn off garbage collection (vacuuming in PSQL parlance).