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Articles tagged: Citus release notes

Today, we’re excited to announce our latest release of our distributed database—Citus 7.2. With this release, we’re making Citus more of a drop-in replacement for your single-node Postgres database, so you don’t need to adapt your SQL for a distributed system.

For multi-tenant applications where the single-tenant queries were scoped to a single machine, Citus already provided full SQL support. . The improvements in Citus 7.2 take our support for distributed SQL one big step further. With Citus database version 7.2, we now extend our distributed SQL support to queries that run on data spread across a cluster of machines. This becomes particularly important for real-time analytics workloads, where even the most complex SELECT queries need to be parallelized across machines.

If you’re into bulleted lists, here’s the quick overview of what’s new in Citus database version 7.2 for distributed queries that span across machines. For an overview of other recent Citus features check out these blogs about distributed transactions and Citus 7.1.

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So about two weeks ago we had a stealth release of Citus 7.1. And while we have already blogged a bit about the recent (and exciting) update to our fully-managed database as a service–Citus Cloud—and about our newly-added support for distributed transactions, it’s time to share all the things about our latest Citus 7.1 release.

If you’re into bulleted lists, here’s the quick overview of what’s in Citus 7.1:

  • Distributed transaction support
  • Zero-downtime shard rebalancer
  • Window function enhancements
  • Distinct ON/count(distinct) enhancements
  • Additional SQL enhancements
  • Checking for new software updates

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“Thirty years ago, my older brother was trying to get a report on birds written that he’d had three months to write. It was due the next day.

We were out at our family cabin in Bolinas, and he was at the kitchen table close to tears, surrounded by binder paper and pencils and unopened books on birds, immobilized by the hugeness of the task ahead. Then my father sat down beside him, put his arm around my brother’s shoulder, and said, ‘Bird by bird, buddy. Just take it bird by bird.’”

Bird by Bird: Some Instructions on Writing and Life, by Anne LaMott

When we started working on Citus, our vision was to combine the power of relational databases with the elastic scale of NoSQL. To do this, we took a different approach. Instead of building a new database from scratch, we leveraged PostgreSQL’s new extension APIs. This way, Citus would make Postgres a distributed database and integrate with the rich ecosystem of tools you already use.

When PostgreSQL is involved, executing on this vision isn’t a simple task. The PostgreSQL manual offers 3,558 pages of features built over two decades. The tools built around Postgres use and combine these features in unimaginable ways.

After our Citus open source announcement, we talked to many of you about scaling out your relational database. In every conversation, we’d hear about different Postgres features that needed to scale out of the box. We’d take notes from our meeting and add these features into an internal document. The list would keep getting longer, and longer, and longer.

Like the child writing a report on birds, the task ahead felt insurmountable. So how do you take a solid relational database and make sure that all those complex features scale? You take it bird by bird. We broke down the problem of scaling into five hundred smaller ones and started implementing these features one by one.

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Star Wars Episode IV Lightsaber image
Image courtesy of Lucasfilm and StarWars.com. © 1977 Twentieth Century Fox.

“Your father’s lightsaber. This is the weapon of a Jedi Knight. Not as clumsy or random as a blaster. An elegant weapon, for a more civilized age.”

—Obi-Wan Kenobi, Star Wars Episode IV: A New Hope

Announcing the release of Citus 6.2

Today I’m happy to announce that we’ve rolled out a new version of our database, Citus 6.2. Because as most of you know, good software never stops evolving. Nor should it. If you want the scoop on the new capabilities in Citus 6.2, just scroll ahead. But before diving in, I need to explain the lightsaber pic. Why? Because usually a picture speaks a thousand words, but sometimes it needs an annotation. :-)

When my colleagues first started on their journey to build Citus, they had a vision of combining the best aspects of relational databases with the elastic scale of NoSQL—to give developers a database that delivers SQL capabilities, at scale.

But vision alone does not make a successful company. The Citus co-founders needed a mix of key ingredients: the right team, good timing, good execution, a willingness to experiment and learn, plus (of course) a good idea.

When George Lucas describes his days before the first Star Wars film, he said he was “searching for just the right ingredients, characters and storyline.” In Lucas’s search for the right mix, he too had to iterate: he wrote four different screenplays before landing on the final version of the original film!

Because our CTO is such a big fan of Star Wars, Ozgun sometimes talks about his vision for Citus in the language of the Jedi: Ozgun has said his aim for Citus was “to create a database as elegant and as powerful as a lightsaber.” Now, I’m more of a Stranger Things fan myself (after all, mornings are for coffee and contemplation) but I get Ozgun’s desire to create a database that gives you the benefits of SQL—at scale.

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Microservices and NoSQL get a lot of hype, but in many cases what you really want is a relational database that simply works, and can easily scale as your application data grows. Microservices can help you split up areas of concern, but also introduce complexity and often heavy engineering work to migrate to them. Yet, there are a lot of monolithic apps out that do need to scale. If you don’t want the added complexity of microservices, but do need to continue scaling your relational database then you can with Citus. With Citus 6.1 we’re continuing to make scaling out your database even easier with all the benefits of Postgres (SQL, JSONB, PostGIS, indexes, etc.) still packed in there.

With this new release customers like Heap and ConvertFlow are able to scale from single node Postgres to horizontal linear scale. Citus 6.1 brings several improvements, making scaling your multi-tenant app even easier. These include:

  • Integrated reference table support
  • Tenant Isolation
  • View support on distributed tables
  • Distributed Vaccum / Analyze

All of this with the same language bindings, clients, drivers, libraries (like ActiveRecord) that Postgres already works with.

Give Citus 6.1 a try today on Citus Cloud, our fully managed database-as-a-service on top of AWS, or read on to learn more about all that’s included in this release.

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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.

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Craig Kerstiens

Announcing Citus 5.2

Written byBy Craig Kerstiens | August 19, 2016Aug 19, 2016

For years we’ve been focused on making Citus the best solution for scaling out your database. We’ve seen customers attain up to 100x performance when compared on the same hardware to vanilla Postgres. Of course you don’t always need to scale out to get good performance–if you have 10 GB of data a single node Postgres can work great. But at data sizes of 100 GB and up, the need to scale out may exist.

Today, with the release of Citus 5.2, it’s now easier to get started earlier so you don’t have to worry about when that moment comes where you won’t be able to scale up further.

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At Citus we want to make dealing with large amounts of operational and analytical workloads easier. Data ingestion speed is key, being the necessary first step in working with any new database. Moreover ingestion is something you’ll do repeatedly in testing and development so the bulk-loading user experience is important as well. With the release of Citus 5.1 the experience in loading data is much better all around, and we’ve managed to sneak in a few other improvements as well. Read more below or give it a try today.

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