4 ms·
Because it was nearly impossible to store all that data before, we had to figure out what we wanted to look at before we got the data. Now that we can store th
by gilbetron 10y ago
Because it was nearly impossible to store all that data before, we had to figure out what we wanted to look at before we got the data. Now that we can store that data easily, it gives us the flexibility to find things we didn't know we wanted. For instance, if you are constantly storing raw sensor and proprioception data for your robot, if you are having problems with, say, its movement routines, you can look at the raw data and look for trends. Imagine how much easier debugging would be if you could just store the state of your software constantly rather than either looking for patterns ahead of time, or just toggling the data dump for small periods of time.
Now instead of a robotic hobbyist, imagine if you were a Tier 1 ISP or large banking institution.
- rdeboo 10y agoTo give a concrete example: My company deploys wireless sensor networks. Each sensor periodically reports its battery status, which we store in a database so we can see which sensors need their battery replaced. Recently we found out that some batteries run empty much quicker than expected. The hardware vendor asked us for 'all battery updates for the past year or so'. We didn't save those; each update was just replacing the current value in the database. So it becomes very hard to diagnose this problem because the historic data is lost.
- thanatropism 10y agoI understand that I have never dealt with really large datasets, whether as a hobby or as a professional (doing econometrics and related analytical work). What it's not clear to me is what TSDBs (such as those listed by Wikipedia; I looked a bit into InfluxDB particularly) do better than RDBMSes. This isn't "negative" skepticism, it's an earnest lack of knowledge.