[120bits]

Interesting read and thanks for sharing.

Not too long ago, I was asked to work on some analytics project and it required time-series data. I'm not a rockstar programmer and don't really know much about trends. So, I ended up googling and stumble upon InfluxDB. It felt like that right choice and I started playing with it. As the time passed, I realized that it might be a good software and I'm sure people love InfluxDB, but it wasn't the right choice for me. I didn't really like the docs, maybe its good now. And I had the same feeling about query syntax, it felt weird.

I moved to TimescaleDB and never looked back. I have it production for almost 2 months now. 20 tables and over 100Million writes/week. One of things I really liked was staging, I don't use docker and or anything fancy. I have bash script that and it runs on centos box and all timescale extension and postgres database are packaged together.

I was impressed by the timescale compression feature. I wasn't using it earlier because I had to be careful about what columns I need to segmentby. I would love to see some more features but I'm sure timescaledb team is already on it.

[mfreed]

Hey 120bits - thanks for the nice words!

What new/other features would you like to see? (Also feel free to join slack.timescale.com or reach out at mike (at) timescale.com)

[jstrong]

to each his own - I find influxdb somewhat flaky but the best part about it is not having to write the atrocious sql queries I would need to to get the same kind of windowed aggregations. `group by time(1h)` and so on is pretty handy.