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We recently integrated TimescaleDB extension into our PostgreSQL database at https://nightwatch.io https://nightwatch.io. For performance reasons, we decided to
by jurgenwerk 9y ago
We recently integrated TimescaleDB extension into our PostgreSQL database at https://nightwatch.io https://nightwatch.io. For performance reasons, we decided to implement time based table partitioning. We were evaluating native PG 10 partitioning vs. TimescaleDB, and concluded the latter will spare us a lot of work, maintenance and headaches. We were right - we got table partitioning basically "for free", query performance improved, and there is no partitioning maintenance involved, everything is automatic behind the curtains with their concept of hypertables. Support is really good too, they are very helpful on Timescale Slack channel.
- akulkarni 9y agoThank you for the kind words, and we are glad to have been helpful to you. Btw anyone is welcome to join the Timescale Slack channel here: http://slack-login.timescale.com/ http://slack-login.timescale.com/
- tda 9y agoI had the same experience. I manually partitioned a pg10 db and it was quite a lot of work to make sure I had all the partitions I need. Then I switched to timescale and got it was just a breeze. I could partition a dataset both in time and in foreign_key with a single command, and performance (especially huge inserts) jumped up. Or to be more accurate, the performance degradation of my table which made each subsequent insert a bit slower than the previous was completely gone. All in all, very happy with timescaledb. Congrats with the funding!
- akulkarni 9y agoThank you!
- tty7 9y agoYup I also had similar experience, have been impressed