July 2018 Newsletter from the Postgres experts at Citus Data

Introducing Landlord: per tenant stats for multi-tenant apps

With Citus 7.5, we’ve gone one step beyond the awesomeness of pg_stat_statements in Postgres. We created the new landlord feature in the Citus database to give you statistics by tenant. Landlord is useful for developers of multi-tenant apps who want insight into whether any tenants are creating load hotspots. Check out this post to learn more about this brand spanking new feature in Citus.
Find out more about landlord →

Options for scaling from 1 to 100,000 tenants

Does this sound like your SaaS application? Your database is performing well at 100 tenants (tenants = customers), your back of the napkin math says you’ll be able to scale your app up to 1,000 tenants, but after that you know you’re going to have to explore some different options to scale. In this post Craig reviews the trade-offs and benefits of different approaches.
More on options for scaling →

High performance distributed DML in Citus

Citus recently added support for UPDATE/DELETE commands with subqueries that span across all the data. Together with the CTE infrastructure that we’ve introduced over the past few releases, this gives you a new set of powerful distributed data transformation commands. As always, we’ve made sure that queries are executed as quickly and efficiently as possible by spreading out the work to where the data is stored.
Marco looks at an example →

All the things coming soon to PostgresOpen SV 2018

If you were not already planning on attending PostgresOpen SV 2018, you might want to make some new plans. Check out Claire’s post on the event. It’s chock full of previews of great talks, tidbits on lovely San Francisco, and a reminder of all that is good about Postgres.
Come join us at PostgresOpen SV →

Using Postgres schemas and views to mask columns with Postgres

In this post, Sai looks at using Postgres schemas and views to provide access to data while keeping Personally Identifiable Information (PII) safe and hidden. He’s discovered that Postgres provides a few primitives that can be used directly within your database to hide PII, while still enabling sophisticated analytics and exploration of data in real time.
Sai shares how to provide data access while keeping personal info private →

ZFS Private Beta on Citus Cloud

We’re excited to announce a private beta of ZFS support in Citus Cloud—for application developers who can benefit from compression in their Postgres database. If you are interested in access to the beta, contact us to get more info, or read this post to learn more about the use cases where ZFS, Citus, and Postgres can help.
Why ZFS for Citus Cloud? →

A distributed geospatial time series database—watch pgDay Paris video of Marco Slot

On his train ride from Amsterdam to Paris for pgDay Paris, Marco Slot fiddled around with three Postgres extensions: pg_partman, PostGIS, and Citus. And he ended up with a pretty good database for real-time analytics on large volumes of geospatial sensor data. Who knew?
Watch the five-minute video →

Watch demo: 10X Faster Analytics Queries on Postgres with Citus

Our engineer Samay Sharma gave yet another good demo, this timeo comparing the performance of analytics queries for a Citus database cluster vs. a single-node database. Samay talks about how Citus shards Postgres—and how query performance scales linearly with the size of the Citus cluster. And we’re jazzed that it was our most popular online demo yet—we had twice as many attendees as Samay’s previous demo. Woot woot!
Watch the 10X demo here →

What one happy open source DBA at RDX says about Citus

Scott B. at RDX says, and I quote, “So, over the last couple weeks, I made IVY, my analysis database, massively parallel - it's stupid fast. I'm not kidding - the folks at citusdata.com are the best - omg - PostgreSQL has never been so entirely ridiculously fast. Thank you so very entirely much.” Scott, you are so very entirely welcome.
See Scott’s post on LinkedIn →

ICYMI: Scalable incremental data aggregation on Postgres and Citus

This post hit the front page of Hacker News, for good reason. In it, Marco walks us through how to build rollup tables in a new and different way, to address the limitations of time windows. Why? So you can easily backfill older events and immediately update the rollup table when new events come in, providing a more real-time view of the data. Sweet!
Marco explains data aggregation on Postgres →

Citans in the wild and some Postgres love

Is Citus right for you?

Want to explore whether Citus is right for you and your use case? Learn more about the Citus product, check out the documentation, or let us know if you want to book a demo.