August 2016 Newsletter from Citus Data

Announcing Citus 5.2

Citus 5.2 is here and it includes a number of great features. Citus 5.2 makes it easier to get started scaling out your data earlier. The highlights of the new release include:

Supporting most major ORMs out of the box
Providing broader SQL coverage
Improving transactional semantics for a single shard

Read more about it on the blog or get started with it today.

PGConf Silicon Valley

PGConf Silicon Valley is just over two months away so make plans to be there now. We’ll be posting the talk schedule next week, and it looks to be another great line-up of talks. Whether you’re looking to learn about Postgres internals, GIS functionality, or get a run down of how it measures up to NoSQL there should be something for you. Don’t wait to grab your ticket because they’re starting to go fast.

Dev plans now available for Citus Cloud

We want the process of scaling your data to be easier–whether it’s Citus 5.2 making it easier for multitenant applications to scale, ORM support, or real-time analytics and search of your data you shouldn’t have to re-engineer everything as your data grows. One part of making it easier is making it less expensive to get started. We’ve now introduced a new dev plan for development, testing, and staging on Citus Cloud. Now you can get started developing with a scalable Postgres database for $99 a month.

On the Blog

Sharding a multi-tenant app with Postgres

A common practice we’ve begun to encounter over and over is the case of a multi-tenant often SaaS application that needs to scale. The scaling issues here are different from that of some real-time analytics as you need to scale out both your memory and processing but also your transactions. As highlighted here there can be some straight forward approaches to this and with Citus 5.2 much of this becomes even easier.

Using State Machines to run Databases

At Citus Cloud we power a number of Citus clusters on top of AWS with fairly robust machinery to help provision, monitor, and manage those instances. This post dives into the fundamental unit of organization we have to manage our service which is concurrent state machines. If you’re curious for a look at how Citus Cloud works under the covers this should start to provide some insight.

Sharding Postgres with semi-structured data and its performance implications

Last month we highlighted a post that walked through some of the differences between hstore, JSON, and JSONB. This month continued exploring JSONB and how you might use it for flexibility as you have the need to look at scaling out your database. This post highlights some of the cases where you may look to use it to scale out a mix or relational and non-relational data.

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