[skibbityboop]

I'm with you, I need to read up more on where timeseries could benefit, at work we have a PostgreSQL instance with around 27 billion rows in a single partitioned table, partitioned by week. Goes back to January of 2017 and just contains tons of data coming in from sensors. It's not "fast", but also not ridiculously slow to say e.g. "Give me everything for sensor 29380 in March of 2019".

I guess depends on your needs but I do think I need to investigate timeseries more to see if it'd help us.

[Too]

Now give me a plot with the average of all sensors of model=A in region=B, grouped by customer, for the past 3 months, downsampled to 500 points. Assuming 1 sensor reading per minute.

I have no doubt sql can do it without too much trouble, but for a time series this is really an instant operation, even on a small server.

A time series will first find the relevant series and then simply for-loop through all the data. It takes just a handful of milliseconds.

Sql will need to join with other tables, traverse index, load wider columns. And you better have set the correct index first, in your case you also spent extra effort on partitioning tables. Likely you are also using a beefy server.

[defrost]

Adding to your comment, from my perspective (exploration geophysics)

> and just contains tons of data coming in from sensors.

it's also desired to, on the fly, deal with missing sensor data, clearly bad sensor data, identify and smooth spikes in data (weird glitch or actual transient spike of interest), apply a variety of running filters; centred average is basic, parameterised Savitzky–Golay filters provide "beefed up" better than running average handling .. and there are more.

It's not just better access to sequential data that makes a dedicated time series engine desirable, it's the suite of time (and geo spatial) series operations that close the deal.

[klaussilveira]

Same boat here, but with DSP/SSP bidding statistics. Generating around 1 billion rows a day and still going strong. Single table, partitioned by week. BRIN index on timestamp, normal index on one column.

Postgres is just a beast.