Ask HN: How do you handle time-series metrics at scale without a large bill?

I want to build my own first party analytics for fun and profit and I'm trying to find a good timeseries database that has a sweet spot between costs, overhead, and scalability.

I've considered just standard PostgreSQL, SQLite on the edge (Cloudflare D1 / Turso), purpose built columnar databases (Clickhouse, DuckDB) and the ones managed by big cloud like Google BigQuery, Amazon Timestream, and Cloudflare Analytics Engine.

For those running event analytics on indie / small-team budgets: what has your actual production experience been? Trying to make an informed decision.

3 points | by xpbl 3 hours ago

1 comments

  • jauco 47 minutes ago
    We’re on azure and a surprisingly good choice has been to use their eventhub to ingest the telemtry and then to consume it in batches of a few seconds using a consumer. Time series is hard because it is a lot of data that comes in all the time, this allows you to relax those requirements a bit.

    After eventhub we’re using ducklake. But I’m not at the point where I’d flat out advise it to other people (just code immaturity that tk their credit is being worked on)

    Also, if you’re evaluating postgres, check out timescaledb.