Learn about Citus on Microsoft Azure in our latest post about use cases: When to use Hyperscale (Citus) to scale out Postgres.

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Articles by Samay Sharma

Samay Sharma

The Postgres 10 feature you didn't know about: CREATE STATISTICS

Written by By Samay Sharma | March 6, 2018 Mar 6, 2018

If you’ve done some performance tuning with Postgres, you might have used EXPLAIN. EXPLAIN shows you the execution plan that the PostgreSQL planner generates for the supplied statement. It shows how the table(s) referenced by the statement will be scanned (using a sequential scan, index scan etc), and what join algorithms will be used if multiple tables are used. But, how does Postgres come up with these plans?

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Samay Sharma

Fermi Estimates On Postgres Performance

Written by By Samay Sharma | September 29, 2017 Sep 29, 2017

A lot of people look to Citus for a solution that scales out their Postgres database, whether on-prem or as open source or in the cloud, as a fully-managed database as a service. And yet, a common question even before looking at Citus is: “what kind of performance can I get with Postgres?” The answer is: it depends. The performance you can expect from single node Postgres comes down to your workload, both on inserts and on the query side and how large that single node is. Unfortunately, “it depends” often leaves people a bit dissatisfied.

Fortunately, there are some fermi estimates, or in laymans terms ballpark, of what performance single node Postgres can deliver. These ballparks apply both to single-node Postgres, but from there you can start to get estimates of how much further you can go when scaling out with Citus. Let’s walk through a simplified guide for what you should expect in terms of the read performance and ingest performance for queries in Postgres.

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