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Comment by vegabook | Hacker News Reader

This is becoming problematic across the open source DB world. Witness the graph capabilities of Datastax Enterprise on top of Cassandra, and Riak TS also took quite a while to open source the "TS" version, hoping I guess to monetize without having to open source. This makes me worried about adopting in case I later get gotcha'd. I am really looking forward to a truly open source time series database. It's not that I don't mind upgrading to enterprise, or paying for services, but the prices end up being so "oracle" like. For example Datastax wants something like 10k per node per year! I mean a credible Cassandra cluster is going to be 5 node bare minimum which really is a lot for a bootstrapping startup.

One of the big problems in the TS world is that KX (KDB) charges an enormous fortune and all the wannabe competitors are salivating at grabbing some of that money.

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Why does the open sources world struggle with timeseries / tick databases so much? I'm a very big KDB fan, but I thought there would be some competition from the open source people at some point, but it seems like every attempt fails. KDB does so well because of its simplicity. Can the OS people not do simple (this is a possible argument), or is it that, as you point out, whenever something is about to be released into the OS sphere the lure of money prevents a full release. Or are they too distracted with the Web and build too many solutions tailored to it. I'm just amazed that a good TSDB hasn't come from the OS crowd yet.

It seems to me that specialised tools will usually be released as a product, because they're only for a specialised niche.

Relational databases are treated like they can store any kind of data, and for small data sets, it really doesn't matter if your data-model does not fit the relational type.

Once you have a larger data set, you're no longer a general purpose user.

KX seems to have a story that is very convincing specifically for financial markets applications.

All the other OSS TSDBs seem to have very good stories for storing server statistics and web clicks, or IoT data; but there are few stories, case studies, best practices for using these in financial applications?

Here [0] is a good blog post and spreadsheet comparing the various open source time series databases.

[0]: https://blog.dataloop.io/top10-open-source-time-series-datab...

Mapd looks really cool but as you say...disincentivized to open source.

What about Druid? It is largely supported by Metamarkets and Yahoo, companies which are not trying to monetise the db itself.

What is KX KDB?

A 'high performance historical time-series columnar database, an in-memory compute engine, and a real-time streaming processor all unified with expressive query and programming language options'

Extensively used in capital markets.

https://kx.com/

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