Citus Blog

Citus is commonly used to scale out event data pipelines on top of PostgreSQL. Its ability to transparently shard data and parallelise queries over many machines makes it possible to have real-time responsiveness even with terabytes of data. Users with very high data volumes often store pre-aggregated data to avoid the cost of processing raw data at run-time. With Citus 6.0 this type of workflow became even easier using a new feature that enables pre-aggregation inside the database in a massively parallel fashion using standard SQL. For large datasets, querying pre-computed aggregation tables can be orders of magnitude faster than querying the facts table on demand.

When we started PGConf Silicon Valley we started it with the goal of helping to grow the Postgres community like many of the other conferences out there with a focus on a large scale west coast event. In our first two years of running the conference...

Citus 6.0 allows you to scale out your transactional relational database with minimal changes to your application, thus reducing complexity over other alternatives while still allowing scale. If you're building a multi-tenant application and outgrow a single node Postgres, by sharding based on tenant with Citus 6.0 you can linearly add more memory and processing power to your database without a large re-architecting of your application. You can still maintain referential integrity, and to your application it's still just standard Postgres.

We recently presented a webcast on when and what to consider when scaling your multi-tenant application. In case you missed it, the recording and slides are below. Within the webcast session, we cover:

It’s a common misconception that high volume read-write workloads in PostgreSQL inevitably causes database inefficiency. We’ve heard of cases where users encounter slowdowns doing only a few hundred writes per second and turn to systems like Dynamo...