Sep 2016 Newsletter from Citus Data

PGConf Silicon Valley

The schedule is live for PGConf Silicon Valley, and it looks great! Take a look at the schedule and start planning which sessions you want to see. There’s still a week to grab your early bird ticket as well so register today and we’ll see you there.

Citus as a Heroku Add-on

Citus Cloud is now available in private alpha as a Heroku add-on. The Heroku add-on will make it easy for you to continue to scale using Citus Cloud, while integrating to the Heroku developer experience. If you’re interested in testing Citus with Heroku reach out and we’ll work to set you up.

Two Factor Authentication: Available (and required) on Citus Cloud

At Citus we want to build a database you can trust. Part of that is ensuring we don’t lose data through monitoring and our minutely backups via continuous protection. Another part is ensuring you can trust your data is safe and secure. With two factor authentication now required on all Citus Cloud production formations we’re taking one more step to help keep you safe.

On the Blog

Building a Scalable Postgres Metrics Backend using the Citus Extension

Citus Cloud uses a Citus Cloud cluster to power metrics fro the service. At this inside baseball post we look at how we’ve designed our data and metrics with Citus so we can provide real-time metrics to all Citus Cloud customers. Whether you’re looking to use Citus Cloud or you want to provide your own real-time analytics across events this is a great highlight of what Citus can provide.

pg_cron: Run periodic jobs in PostgreSQL

Pg_cron is a simple cron-based job scheduler for PostgreSQL that runs inside the database as an extension. It uses the same syntax as regular cron, but it allows you to schedule PostgreSQL commands directly from the database. If you have the need for running jobs on a regular basis such in database rollups, vacuum, or the shard rebalancer then give pg_cron a look.

Fun with SQL: Computing run rate and month over month growth

Here’s a walk through of a fairly complex query which calculates run rates and percentage growth rate over time for an ‘as-a-service’ business. It breaks the query apart step by step and leverages a number of Postgres features such as CTEs and window functions.