promscale

There's a big difference -- that's how the PostgreSQL community works. 2ndQuadrant (now EDB), EDB, Citus (now Microsoft) all add value to open source Postgres, contribute back to the community by bringing new features, new life, usecases, and of course committing changes upstream where possible. Timescale is actually on the more open side of that balance, with the licensing and the community version feature matrix. Also, in this case, Timescale actually has a pretty forgiving license[0] as long as you are not a add-nothing-aaS-provider, perhaps more than it should be, which I've asked about before[1]. Even before that change was made, running just the community edition as a add-nothing-aaS-provider would have been an improvement on the status quo, given how soundly it thrashed some other solutions in the past (ex. Influx[2]) and what you

> TimescaleDB is purpose-built for time-series workloads, so that you can get orders of magnitude better performance at a fraction of the cost, along with a much better developer experience. This means massive scale (100s billions of rows and millions of inserts per second on a single server), 94%+ native compression, 10-100x faster queries than PostgreSQL, InfluxDB, Cassandra, and MongoDB – all while maintaining the reliability, ease-of-use, SQL interface, and overall goodness of PostgreSQL. WITH the links to back up their analysis/comparisons. I think I was first sold the hardest on Timescale when I read the InfluxDB post. Timescale also releasing their hard work over the last ~3 years with a very permissive, surprisingly business friendly license[0] which was previously discussed on HN[1]. This is pretty huge -- personally one of the t

TimescaleDB is a long-term storage option for Prometheus metrics, has no problem with high-cardinality, and now natively supports PromQL (in addition to SQL) [0] (Disclaimer: I work at Timescale) [0] https://github.com/timescale/timescale-prometheus

We have quite a few in our Slack channel: slack.timescale.com Feel free to ask over there :) (Btw - TimescaleDB is designed to work with Prometheus. You can see more here: https://github.com/timescale/timescale-prometheus)

There are number of tools, which can be used in front of TimescaleDB or PostgreSQL. There are plugins for Telegraf, Kafka, Prometheus as described in https://docs.timescale.com/latest/using-timescaledb/ingestin... Timescale builds connector and entire workflow to run Prometheus on top of TimescaleDB and support Grafana in flexible way: https://github.com/timescale/timescale-prometheus

I was testing out both TimescaleDB/InfluxDB recently, including maybe using with Prometheus/Grafana. I was leaning towards Timescale, but InfluxDB was indeed a lot easier to quickly boot a "batteries included" setup and start working with live data. I eventually spent a while reading about Timescale 1 vs 2, and testing the pg_prometheus[1] adapter and started thinking through integrating its schema to our other needs then realizing it's "sunsetted" and then reading about the new timescale-prometheus[2] adapter and reading through its ongoing design doc[3] with updated schema that I'm less a fan of. I finally wound up mostly-settling on Timescale although I've put the Prometheus extension question on hold, just pulling in metrics data and outputting with ChartJS and some basic queries got me a lot closer to done for now. Our use case may b

(Timescale-Prometheus team lead here) I'd suggest using Timescale-Prometheus to connect Prometheus with TimescaleDB. Repo: https://github.com/timescale/timescale-prometheus Design Doc: https://tsdb.co/prom-design-doc

You can use Prometheus on top of TimescaleDB. Timescale builds connector and entire workflow to run Prometheus on top of TimescaleDB and support Grafana in flexible way. Sorry for the promo :) check for details in https://github.com/timescale/timescale-prometheus

Because TimescaleDB is a relational database for general-purpose time-series data, it can be used in a wide variety of settings. That configuration you cite isn’t for the core TimescaleDB time-series database or internals, but to add a specific configuration and setup optimized for Prometheus data, so that users don’t need to think about it and TimescaleDB can work with the specific Prometheus data model right out of the box. Those “scripts” automatically setup a deployment that is optimized specifically to have TimescaleDB serve as a remote backend for Prometheus without making users think about anything. Some databases would need to write a lot of specific internal code for this; TimescaleDB can enable this flexibility through configuring proper schemas, indexes, and views instead (in addition to some specific optimizations we've done t

I don't consider TimescaleDB to be a serious contender as long as I need a 2000 line script to install functions and views to have something essential for time-series data like dimensions: https://github.com/timescale/timescale-prometheus/blob/maste... https://github.com/timescale/timescale-prometheus/blob/maste...

Absolutely! We wrote one of the first remote backends to Prometheus that supports both the remote_read/remote_write interface: https://prometheus.io/docs/operating/integrations/#remote-en... Given how much interest we had using TimescaleDB for this, we recently built and released (in beta) a new "full-stack" of Prometheus + TimescaleDB + Grafana that comes fully configured and "just works" out-of-the-box: - https://tsdb.co/prom-design-doc - https://github.com/timescale/timescale-prometheus