3 ms·
> They're not directly comparable, but kdb+ would crush InfluxDB head to head in an apple/orange comparison if used for the same thing. I actually can't think o
by _pmf_ 11y ago
> They're not directly comparable, but kdb+ would crush InfluxDB head to head in an apple/orange comparison if used for the same thing. I actually can't think of any time series-like store that remotely comes close to the feats I have seen kdb+ with Q accomplish. Too bad the productivity and knowledge overhead is so high.
Do you have any more specific use cases for the kind of analysis that kdb+ is used for? I'm working with timeseries sources that represent streams from internal variables from embedded systems and would like to evaluate whether kdb+ brings something to the table that we could use. (What we are doing probably falls into the category Complex Event Processing, i.e. windowed operations on the data stream with some predicates being evaluated globally.)
- icsa 11y agoOne very important use case is the asof join. i.e. - "line up" two or more time series by time so that they can be compared or analyzed together. kdb+ does this very efficiently.
- icsa 11y agoCould you provide representative CEP use cases? I may be able to provide some insight.
- gricardo99 11y agokdb+/q is great for this sort of thing (data stream processing and analytics). The "traditional" kdb+ example/benchmark, is some query on big data, and it excels at that. But another use case is to setup several real-time kdb+ processes, like a processing pipe-line, or distributed work-load, that react to real-time messages/events, and produces some output (derived analytic, alert, action, etc...). One example is trading, where you have real-time market data being sent to some kdb+ processes, which run some analytic/rules, and issue/manage orders sent to the market. It takes surprisingly few lines of q code to set something like this using kdb+.