Citus Blog

One of the unique things about Postgres is that it is highly programmable via PL/pgSQL and extensions. Postgres is so programmable that I often think of Postgres as a computing platform rather than just a database (or a distributed computing platform—with Citus). As a computing platform, I always felt that Postgres should be able to take actions in an automated way. That is why I created the open source pg_cron extension back in 2016 to run periodic jobs in Postgres—and why I continue to maintain pg_cron now that I work on the Postgres team at Microsoft.

Using pg_cron, you can schedule Postgres queries to run periodically, according to the familiar cron syntax. Some typical examples:

I recently analyzed the limits of connection scalability, to understand the most effective way to improve Postgres' handling of large numbers of connections, and why that is important. I concluded that the most pressing issue is snapshot scalability.

This post details the improvements I recently contributed to Postgres 14 (to be released Q3 of 2021), significantly reducing the identified snapshot scalability bottleneck.

As the explanation of the implementation details is fairly long, I thought it'd be more fun for of you if I start with the results of the work, instead of the technical details (I'm cheating, I know ;)).

One common challenge with Postgres for those of you who manage busy Postgres databases, and those of you who foresee being in that situation, is that Postgres does not handle large numbers of connections particularly well.

While it is possible to have a few thousand established connections without running into problems, there are some real and hard-to-avoid problems.

Since joining Microsoft last year in the Azure Database for PostgreSQL team—where I work on open source Postgres—I have spent a lot of time analyzing and addressing some of the issues with connection scalability in Postgres.

Making security easy to use is crucial because hard-to-use security is likely to be neglected entirely. SCRAM with channel binding is a variation of password authentication that is almost as easy to use, but much more secure.

In basic password authentication, the connecting client simply sends the server the password. Then the server checks that it's the right one, and allows the client to connect. Basic password authentication has several weaknesses which are addressed with SCRAM and channel binding.

In this article, you'll learn how to set up authentication using SCRAM with channel binding in Postgres. I implemented the client connection parameter channel_binding in PostgreSQL 13, due to be released in late 2020 (PostgreSQL 13 is in beta now). SCRAM and Channel Binding have already been supported in several releases, but this new connection parameter is necessary to realize the security benefits of SCRAM and Channel Binding.

Interview with the Postgres committers who have joined the Postgres team at Microsoft by Sudhakar Sannakkayala (Partner Director, Azure Data) and Ozgun Erdogan (Principal, Azure Data)—cross-posted from the Azure Database for PostgreSQL Blog.

In recent years, the data landscape has seen strong innovation as a result of the onset of open source technologies. At the forefront, PostgreSQL has shown that it’s the open source database built for every type of developer. By staying true to its principles of being standards-compliant, highly programmable, and extensible, PostgreSQL has solidified its position as the “most loved database” of developers across the board—ranging from scenarios for OLTP, analytics, and business intelligence to processing various formats of geometric data using the PostGIS extension.