The simple deployment and upgrade processes. The ability to manage dynamic data with varying variables/sensors per row.

QuestDB and it's development team have enabled us to shape our product to our liking. We are working with very large datasets 6000+ columns x 150 rows per second and questdb has enabled us to ingest that quickly. This one feature cannot be understated as we found ourselves limited by an SQL restriction of 4096 columns in other databases. In our year of using QuestDB, the development team has made tremendous progress. In a recent release, a commit was made "5x speed up of WAL Apply for small transaction and add SQL" that opened up a whole new world of speed for us. If you tried it before and it wasn't quite there yet, I would reccomend trying it again, as this single update really allow us to be near livestreaming of all this data. We love that QuestDB uses a SQL backend, as that enables us to quickly bring new team members up to speed. Another huge benefit has been QuestDBs developer connected slack channel. When things have gone wrong, the developers at QuestDB have been quick to step in and provide feedback (generally on what we are doing wrong! haha). Occasionally we have had real bugs, and have seen a direct improvements in the next release cycle. Another benefit we've found has been the variety of languages QuestDB supports. We were quick to integrate with a pandas ingestion libaray and have been off to the races since.

As a quant researcher that need to monitor and diagnose details from high frequency sampling of market and trading data, QuestDB has proved to be reliable, performant and easy to use. Specifically I like 1. Helpful time series features that neatly fit the use cases in high frequency trading. E.g. the symbol data type, the sample by, asof join, the window function(could be more complete) etc. 2. High efficiency so that don't need to spend much on the hardware. A couple of hundred million rows with wide columns on a 4-core box serve my needs pretty well 3. Some user-friendly features that makes it easy to get data into the DB. Specifically I like the the flexible table schema, which caters to the need for constantly evolving data columns. The web UI is nice (though could be more polished). The InfluxDB line protocol supports very simple python code to upload pandas dataframes.