However, last time I looked that didn't seem like a use case InfluxDB invested a ton of effort optimizing for, especially if you tried to store a lot of separate "event histories" either as separate measurements or by using tags. By "a lot" I mean 100K-100M histories. It may have improved since.
Besides, there is somewhat fundamental tradeoff between allowing efficient realtime granular writes, which I believe a priority for InfluxDB, and building efficient indexed store for millions of histories/event trails, which is more of a TrailDB use case. Kind of OLAP vs OLTP.
However, last time I looked that didn't seem like a use case InfluxDB invested a ton of effort optimizing for, especially if you tried to store a lot of separate "event histories" either as separate measurements or by using tags. By "a lot" I mean 100K-100M histories. It may have improved since.
Besides, there is somewhat fundamental tradeoff between allowing efficient realtime granular writes, which I believe a priority for InfluxDB, and building efficient indexed store for millions of histories/event trails, which is more of a TrailDB use case. Kind of OLAP vs OLTP.