[tnolet]

We adopted ClickHouse ~4 years ago. We COULD have stayed on just Postgres. With a lot of bells, whistles, aggregation, denormalisation, aggressive retention limits and job queues etc. we could have gotten acceptable response times for our interactive dashboard.

But we chose ClickHouse and now we just pump in data with little to no optimization.

[xmodem]

We migrated some analytics workloads from postgres to clickhouse last year, it's crazy how fast it is. It feels like alien technology from the future in comparison.

[apwell23]

are those like embedded analytics in the app or internal BI type workloads ?

[tnolet]

For us these are just metrics on customer facing dashboards inside our app. They are basically realtime and show p95, p99, avg. etc over time ranges. Our app can show this for 1000s of entities in one dashboard and that can eat up resources pretty quickly

[nasretdinov]

I imagine with Postgres there's also an option of using a plugin like Greenplum or something else, which may help to bridge the gap, but probably not to the level of ClickHouse.

[tnolet]

yes, we looked at Timescale also. But they were much younger then and Clickhouse was more mature. Clickhouse cloud did not exist yet. We now use a mix of Altinity and Cloud.

[tucnak]

There's foreign data wrappers for Clickhouse that still allow Postgres as single point of consumption with all the benefits of Clickhouse deployment.

This is how we consume Langfuse traces!