The second and more important one relates to auto failover. The first is the complexity associated with it: it takes twelve steps to setup streaming replication, and you may also need to understand concepts such as the number of wal segments and replication lag in the process. When you talk to users who use streaming replication in production, they express two pain points with it. It then ships those changes to one or more secondary nodes for them to apply. The primary node takes all writes and executes all changes against the database. Streaming replication works by designating one PostgreSQL instance as the primary node. PostgreSQL provides streaming replication as a way to provide high availability since its v9.0 release. I’d like my PostgreSQL database to be Highly Available Since Citus is an extension to Postgres (not a fork), it makes sense to start with a pain most Postgres users have. Although we describe these learnings in the context of Postgres, Citus, and AWS, they are also applicable to other databases and cloud vendors. In the following, we’re going to talk about each one of these seven points as a mini-learning. We then started breaking down each customer conversation into smaller pieces and found that our customers had seven operational pain points. Early on, we thought that our customers were asking for something that was more magical than attainable – Citus should handle failovers in a way that’s transparent to the application, elastically scale up and scale out, take automatic backups for disaster recovery, have monitoring and alarms built in, and provide patches and upgrades with no downtime. The following sections highlight our learnings from talking to hundreds of prospective customers. In this blog post, we’ll only focus on removing operational pain points and not on use cases: Why is cloud changing the way databases are delivered to customers? What AWS technologies Citus Cloud is using to enable that in a unique way? It turns out that targeting an important use case for your customers and delivering it to them in a way that removes their pain points, matters more than anything else. (Honestly, if the founding engineers of the Heroku Postgres team didn’t join Citus, we might have decided to wait on this.) After having Citus Cloud publicly available for eight months though, we are now more bullish on the cloud then ever. Naturally, we were also worried that providing a native database offering on AWS could split our startup’s focus and take up significant engineering resources. To remove these operational barriers, we’ve been thinking about offering Citus as a managed database for a while now. One challenge associated with building a distributed relational database (RDBMS) is that they require notable effort to deploy and operate. And as always, the Citus database is also available as open source: you can find the Citus repo on GitHub or download Citus here.Ĭitus is a distributed database that extends (not forks) PostgreSQL for large workloads. If you’re looking to distribute PostgreSQL in the cloud (for multi-tenant SaaS apps, or real-time analytics, or time series workloads), take a look at Azure Cosmos DB for PostgreSQL. Update in October 2022: The Citus managed database service is now available in Azure Cosmos DB for PostgreSQL.
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