Citus Blog

Citus enables several different PostgreSQL use cases, but one of the most popular ones is to build scalable multi-tenant software as a service (SaaS) applications. The most common way to build a multi-tenant application on Citus is to distribute all your Postgres tables by a “tenant ID” column. That way rows are (hash-)distributed across nodes, while rows with the same tenant ID value are co-located on the same node for fast local joins, transactions, and foreign keys.

For those of you who build SaaS apps, one question many of you have is how active your tenants are. More specifically: What are your busiest tenants? How many queries is your application doing on behalf of your tenants, and how much CPU do those queries use?

The new 11.3 release to the open source Citus database extension gives you tenant monitoring—with instant visibility into your top tenants using the new citus_stat_tenants feature, which shows query counts and CPU usage over a configurable time period.

Keep reading

Relational databases are the first choice of data store for many applications due to their enormous flexibility and reliability. Historically the one knock against relational databases is that they can only run on a single machine, which creates inherent...

Keep reading

Whether you’re building marketing analytics, a portal for e-commerce sites, or an application to cater to schools, if you’re building an application and your customer is another business then a multi-tenant approach is the norm. The same code runs for all customers, but each customer sees their own private data set, except in some cases of holistic internal reporting.

Early in your application’s life customer data has a simple structure which evolves organically. Typically all information relates to a central customer/user/tenant table. With a smaller amount of data (10’s of GB) it’s easy to scale the application by throwing more hardware at it, but what happens when you’ve had enough success and data that you have no longer fits in memory on a single box, or you need more concurrency? You scale out, often painfully.

Keep reading