Citus Blog

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...

We talk with a number of Postgres users each week that are looking to scale out their database. First, we would never recommend scaling out until you truly have to, it’s always easier to scale your database up rather than out. It’s often not until over 100 GB of data that you need to think about sharding.

When you want to scale out though, you want it to be simple. For scaling a multi-tenant database, there’s three common approaches:

Citus is a distributed database that extends (not forks) PostgreSQL. Citus does this by transparently sharding database tables across the cluster and replicating those shards.

After open sourcing Citus, one question that we frequently heard from users related to how Citus replicated data and automated node failovers. In this blog post, we intend to cover the two replication models available in Citus: statement-based and streaming replication. We also plan to describe how these models evolved over time for different use cases.

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...

PGConf Silicon Valley, November 14-16, is barely under a month away and it's shaping up to be another great conference this year. Last year we had over 300 attendees to make it one of the larger Postgres conferences around, and this year we're expecting...

Everybody counts, but not always quickly. This article is a close look into how PostgreSQL optimizes counting. If you know the tricks there are ways to count rows orders of magnitude faster than you do already.

The problem is actually underdescribed...