

gauged: a time series database - chrisohara
https://github.com/chriso/gauged/tree/master

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otterley
Interesting storage method; I like it. Some notes:

\- A MySQL backend should be very fast, but scaling it into multiple shards
will have to be an exercise for the user. Perhaps CitusDB (PostgreSQL
compatible) could be useful here.

\- Metrics cannot be tagged. This will make it useless for any sort of rollups
or breakdowns ("give me the sum of requests over my servers in the XYZ data
center"; "give me the requests for each server in the XYZ data center by
hostname").

The second issue in particular needs attention before it can complete with
enterprise-grade metrics solutions such as Datadog.

~~~
chrisohara
Tagging would be the next addition. I added the ability to search for keys by
prefix quite efficiently, so provided one stored keys like "requests:server1",
"requests:server2", one could easily run the following

    
    
        requests = 0
        for key in gauged.keys('requests:'):
            requests += gauged.aggregate(key, Gauged.SUM, start=-Gauged.WEEK)

~~~
otterley
Tagging needs to be multi-dimensional to be effective (e.g., host=X, device=Y,
interface=Z, etc.)

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rlpb
I'd love to see an honest comparison against RRDtool. You mention it once in
"Support for sparse data (unlike the fixed-size RRDtool)".

What are the other advantages, disadvantages and trade-offs?

