At my employer, we've recently (as of the middle of last year) been making a considerable effort to use InfluxDB to track our KPIs. It's working out wonderfully for us, and I'm expecting it'll get used more and more as the year goes on.
What really floors me about Influx is how fast it is. A query that used to take hours in Oracle takes seconds in Influx. And the influx query is readable: rolling data up to various intervals produced nightmare queries in Oracle but is short and sweet in Influx. Want to take data gathered every 5 minutes and give a daily average? Yeah, good luck with that in Oracle. It's doable, sure, but I've seen the code. And the speed. Both are ugly.
The only problem I have with InfluxDB is it's still a little immature, and the tooling isn't where it should be. This isn't entirely Influx's fault; most third parties aren't aware it exists or don't care. Our reporting team uses Crystal Reports, which can't talk to InfluxDB. So I end up having to write a Python script that runs in cron every night to perform InfluxDB queries for the previous day's data doing all the rolling and average/min/max calculations and then inserting the results into Oracle, just so our reporting team can get to the data. For some KPIs I'm working on right now, we decided to not go through the reporting team, and I'm writing a webapp in Python/Bottle to display the report, and we're probably going to augment that with graphs from Grafana.
How big is your database, and how long does it take to restart? We have what I would describe as a fairly small influx database, and it takes a long time to restart (20-30 mins). And the time to restart seems to be growing linearly with the db size. Not cool if you do regular server patching with reboots.
We also had a problem where user queries that return too many columns cause the DB server process to OOM. And then it restarts, so another 20 mins of downtime. Also not cool.
We liked the tagging and rollup features, and automatic retention management, but those first 2 problems really turned us off.
I can attest to how great InfluxDB is. Have used it in a few applications that rely on time based data and I am constantly blown away by how fast the query times are.
I think you're saying a lot more about Oracle than about Influx :)
I also am using Influx at my company and the experience is not that great, mostly due to it being immature yes. For example, I currently have runaway disk usage and I have no way to know what table is using it. So I have to choose between losing data or continuously increasing storage.
One bit of immaturity I just remembered: InfluxDB does a terrible job of telling you when you've fat-fingered a query. You can select from a series that doesn't exist or reference a tag that doesn't exist inside a 'where' clause, and InfluxDB will happily return 0 results instead of giving an error.
I've spent some time trying to figure out why I'm not getting data, and it turns out that it was because I typoed the name of the series.
What really floors me about Influx is how fast it is. A query that used to take hours in Oracle takes seconds in Influx. And the influx query is readable: rolling data up to various intervals produced nightmare queries in Oracle but is short and sweet in Influx. Want to take data gathered every 5 minutes and give a daily average? Yeah, good luck with that in Oracle. It's doable, sure, but I've seen the code. And the speed. Both are ugly.
The only problem I have with InfluxDB is it's still a little immature, and the tooling isn't where it should be. This isn't entirely Influx's fault; most third parties aren't aware it exists or don't care. Our reporting team uses Crystal Reports, which can't talk to InfluxDB. So I end up having to write a Python script that runs in cron every night to perform InfluxDB queries for the previous day's data doing all the rolling and average/min/max calculations and then inserting the results into Oracle, just so our reporting team can get to the data. For some KPIs I'm working on right now, we decided to not go through the reporting team, and I'm writing a webapp in Python/Bottle to display the report, and we're probably going to augment that with graphs from Grafana.
Grafana is beautiful, by the way.