Hi, I'm Adam Cimarosti, one of the core engineers at QuestDB.

We built play.questdb.io to make it easy for anyone to try our database. No installation.

There's a Jupyter Lab notebook, data, sample code, queries and graphs.

We'd love to hear what you think.

Reading your pitch here, i'd love to have a vague idea what questdb is and why I should care.

Most databases store the latest state of something. We don't. We ingest events. After all, life is a function of time :-) The whole world ticks and we take those ticks and store them. If part of your application tracks anything happening over time (trades, ocean pollution levels, ships moving, rocket simulation metrics.. or whatever else then it makes sense to store those events in a time series database. What we provide, primarily, is two basic pieces of functionality: (1) Taking in lots of events FAST. Our ingestion rate is high (and we also integrate with things like Kafka, Pandas -- see the notebook, etc). Each of our time series tables (we support regular ones too) comes with a special timestamp column. (2) Specialized SQL to make sense of data that's changed over time, such as grouping and resampling by time and more. Take a look at our docs for things like SAMPLE BY, LATEST ON, ASOF JOIN, LT JOIN and more. On disk, we also guarantee that all records are sorted by time and this gives us great query performance for these time-based types of queries.

PS. We're also wire-compatible with PostgreSQL.

So I guess it would be fair to say you compete with Timescale and Clickhouse as a timeseries database?