
Building a Scalable Postgres Metrics Backend Using the Citus Extension - mmcgrana
https://www.citusdata.com/blog/2016/08/30/citus-clouds-usage-of-citus-cloud/
======
devbug
If you haven't already seen it, Dan from Heap Analytics has a great talk about
how they use Postgres and Citus.

[https://www.youtube.com/watch?v=NVl9_6J1G60](https://www.youtube.com/watch?v=NVl9_6J1G60)

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doh
We[0] just recently moved from Hbase to Postgres w/ Citus. Still not fully
settled in, but got incredible support from the Citus team (seriously amazing
guys) and things are looking much brighter than before.

On a 8 worker nodes (16 cores, 80GB ram, 3TB SSD), we're at around 20k
inserts/second, while most of the selects are running at around 100ms (besides
some counts and complex queries).

If you have a lot of data and know Postgres, give it a chance.

[0] [https://pexe.so](https://pexe.so)

~~~
koolba
> On a 8 worker nodes (16 cores, 80GB ram, 3TB SSD), we're at around 20k
> inserts/second, while most of the selects are running at around 100ms
> (besides some counts and complex queries).

Is that 20K separate transactions or are some of the 20K inserts grouped
together?

~~~
doh
Separate (going through the master).

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sciurus
If you're looking for a metrics backend built on traditional Postgres, check
out Tgres.

[http://grisha.org/blog/2016/07/29/state-of-
tgres-2016/](http://grisha.org/blog/2016/07/29/state-of-tgres-2016/)

~~~
GrayTShirt
+1 for tgres [https://github.com/tgres/tgres](https://github.com/tgres/tgres)
On an aside, I found his posts on holt-winters very informative.

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kornish
For anyone with questions about how to properly shard a table, how to fit a
problem to a distribution strategy, or general questions about deployment,
Citus has a Slack channel which is active and extremely welcoming. You can
request an invite here:
[https://slack.citusdata.com/](https://slack.citusdata.com/)

Disclaimer: don't work there, but on the Slack and the Citus team is nothing
short of awesome.

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dataloopio
I had a look at Citus when evaluating time series databases and the documents
said that work was still under way on masterless setup for faster ingestion
(up to 500k metrics /sec).

[https://docs.citusdata.com/en/v5.2/performance/scaling_data_...](https://docs.citusdata.com/en/v5.2/performance/scaling_data_ingestion.html#masterless-
citus-50k-s-500k-s)

If that has changed I'd add it to my table.

[https://docs.google.com/spreadsheets/d/1sMQe9oOKhMhIVw9WmuCE...](https://docs.google.com/spreadsheets/d/1sMQe9oOKhMhIVw9WmuCEWdPtAoccJ4a-IuZv4fXDHxM/edit#gid=0)

