InfluxDB, the most popular time-series database, is optimised for a very specific kind of workloads: many sensors publishing frequently to a single node, and frequent queries that are not going far back in time. It's great for that. But it doesn't support doing slightly advanced queries such an average over two sensors. It also doesn't scale and is pretty slow to query far back in time due to its architecture.
TimeScaleDB is a bit more advanced, because it's built on top of PostGreSQL, but it's not very fast. It's better than vanilla PostGreSQL for time-series.
The TSM Bench paper has interesting figures, but in short ClickHouse wins and manage well in almost all benchmarks.
https://dl.acm.org/doi/abs/10.14778/3611479.3611532
Unfortunately, the paper didn't benchmark DuckDB, Apache IoTDB, and VictoriaMetrics. They also didn't benchmark proprietary databases such as Vertica or BigQuery.
If you deal with time-series data, ClickHouse is likely going to perform very well.