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I find clickhouse with proper time-series encoding and tiered data storage to be a better alternative than timescale. There were also some issues with ingestion speed with a timescaleDB.

Can we think of timescale as OLTP for timeseries data with gurrantees from postgres and clickhouse as OLAP for timeseries data?

Continuous Aggregates is a neat feature though.

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Clickhouse is a really great piece of technology, especially for general OLAP.

But for time-series workloads, we've found that the results are quite close, with TimescaleDB outperforming Clickhouse for many different types of query workloads. We'll be sharing our results soon.

Nice to hear! We are looking for cases where ClickHouse is not as fast as it could be. And we you can share your experience with ClickHouse on GitHub issues or by mail. If something was not intuitive or worked not as expected. Or lack in functionality

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