It allows you to define aggregations that are automatically used when quering the raw table if the query matches, and it also allows you to drow the raw data with a retention policy but keep the aggregated form (https://docs.timescale.com/latest/using-timescaledb/continuo...)
So what that means is that TimescaleDB has mechanisms to make it really easy to define downsampling (continuous aggregates, data retention policies), and even have queries that transparency query across the historical aggregates and new raw data (real-time aggregates, which parent pointed to, which isn't supported by InfluxDB).
What the database _by itself_ doesn't do is automatically create certain continuous aggregates on metrics immediately, because frankly, users' needs vary so much.
That said, we have built stacks/solutions that leverage TimescaleDB and do precisely that. For example, we just released a design doc and beta around our refreshed native integration with Prometheus, that addresses an extremely similar use case to Graphite / rrdtool. Because now this is automated, it defines many of these things out-of-the-box, so you don't need to configure anything. Check it out and input welcome!
- See https://github.com/timescale/timescale-observability
- Or join the #prometheus channel at https://slack.timescale.com