17 ms·

I believe Timescale has a similar issue if you’ve enabled compression (and it’s usually too expensive not to). Perhaps the main reason we’re sticking with Influ

• akulkarni 6y ago
  (Timescale person) You can backfill or update data that lives in a compressed chunk by first decompressing that chunk. [0] But we are working on making it easier. :-) [0] https://docs.timescale.com/latest/using-timescaledb/compression#decompress-chunks https://docs.timescale.com/latest/using-timescaledb/compress...
  • jeremycarter 6y ago
    We have compression enabled for data older than 3 months. This gives us enough wiggle room to insert/modify anything recent.
• valyala 6y ago
  Take a look also at VictoriaMetrics - it supports loading historical data without any restrictions [1]. It supports Influx line protocol for data ingestion [2] and it usually requires lower amounts of RAM / CPU / disk space comparing to InfluxDB [3]. [1] https://victoriametrics.github.io/#backfilling https://victoriametrics.github.io/#backfilling [2] https://victoriametrics.github.io/#how-to-import-time-series-data https://victoriametrics.github.io/#how-to-import-time-series... [3] https://medium.com/@valyala/insert-benchmarks-with-inch-influxdb-vs-victoriametrics-e31a41ae2893 https://medium.com/@valyala/insert-benchmarks-with-inch-infl...