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Perhaps I'm wrong, but "timeseries" databases are typically some combination of LSM style append only logs and eventual consistency. In an ACID relational database, i'm not sure you can simultaneously write and read millions of rows per second? If you can I'd love to learn something new :)

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You can write several million rows per second through indexing and storage while reading consistent views but it is not trivial. It requires a pretty sophisticated database kernel design even on modern hardware. LSM-style is not a good choice if you require these write rates. Time-series data models are relatively simple to scale writes for as such things go.

I would not want to try this on a traditional relational database kernel, they are not designed for workloads that look like this. They optimize their tradeoffs for slower and more complicated transactions.

But doesn't TimescaleDB maintain all the guarantees of ACID?

They do you can do some pretty good optimizations if you know what type of data is being written to a table, and with Timescale, you are converting a specific table into a Timescale hypertable, which give you different tradeoffs from a standard Posgresql table. End result is really great performance for inserts and queries while maintaining ACID guarantees.

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