Earlier quoted context omitted.
I wouldn't choose InfluxDB over TimescaleDB. There's a reasonably balanced comparison here from the Timescale guys: https://blog.timescale.com/blog/timescaledb-vs-influxdb-for-... The benchmarks are interesting, showing TimescaleDB to be the clear winner in most scenarios. For me that's nice, but it's a bigger deal to me personally that I already have Postgres and SQL experience that translates directly to TimescaleD…
Agree totally on the "double down on what you know" point. That pays off in spades usually. Tangentially related to that: their mongo benchmark numbers always looked odd to me. Given that I've used mongo for 10+ years for high throughput time series data without major issues, I decided to do my own benchmarks. In my testing, mongo outperformed timescale significantly both in write throughput and query performance. Th…
Always strive to do the best and fairest benchmarks we can, and for that reason, all our benchmarks are fully open-source for both repeatability and improvements/contributions:
https://github.com/timescale/tsbs/blob/master/docs/mongo.md
We also really did spend a lot of time investigating approaches with MongoDB, so you'll see our benchmarks actually evaluate two _different_ ways to use time-series data with MongoDB (culled & optimized from suggestions in MongoDB forums). But always welcome to feedback:
https://blog.timescale.com/blog/how-to-store-time-series-dat...
Thanks!