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Comment by olviko | Hacker News Reader

What are the benefits of introducing specialized time-series databases vs using Redis, Casandra, or some Sql database?

One way to think of it is why would you use Cassandra when you already have a filesystem?

Those databases are quite raw, to be useful for a use case like monitoring you need to build on top of them to allow for ability to get data from agents, do some processing and enable efficient querying of the data.

The answer to this question would be extremely long, so I suggest you first brush up on some fundamentals of database design.

http://www.slideshare.net/bijugs/row-or-columnar-based-datab...

then go onto getting mad at Michael Stonebraker here:

https://gigaom.com/2013/12/14/5-predictions-on-the-future-of...

and then when you realize he's right about everything, you'll have the foundational knowledge to understand the problem a little bit better.

Very few if any if your talking Cassandra (I would never store time series in redis), I worked developing TSD and are active in the space, most companies goes with Cassandra these days and builds computational frameworks upon that.

Just curious, why not Redis?

I'm not him obviously but...

If you are at the scale you can't dump it on just 1-2 nodes and call it a day [which is when you are start looking at Cassandra or a dedicated TSD] ...you really need 3 DC availability usually and Redis simply cannot do that in any reasonable way.

Even if you don't need a dedicated TSD with redundancy - Redis would still be more expensive to run given that you you would need to keep everything in memory. Given that you won't read 90% of the data most of the time, it makes little sense to store all of it in memory

InfluxDB can downsample on the fly, to name an example. Functionality like this out of the box can be pretty handy, otherwise you have to build it yourself.

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