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CockroachDB debuted as the open source database that made it possible to build massive, reliable cloud applications without giving up SQL. Forward-thinking companies adopted it to hide the complexity of dealing with distributed scale, resilience, and consistency problems in the database layer. The promise was simple: keep your apps simple and your pagers silent. Over the last six months, we’ve welcomed Mesosphere as a customer and helped companies like Kindred and Baidu continue to migrate internet-scale workloads onto CockroachDB. We’ve also watched our distributed SQL database enable exciting new use cases, from a blockchain solution for certifying document authenticity to a system of record for tracking simulations that help optimize oil and gas exploration.

Nate Stewart

April 4, 2018

Correctness, stability, and performance are the foundations of CockroachDB. We've invested tremendous resources into correctness and stability. Today, performance takes the spotlight as we will be publishing benchmarked metrics that demonstrate that you can achieve correctness, stability, and excellent performance within the same database.

Andy Woods

March 29, 2018

We are excited to announce support for JSON in our 2.0 release (coming in April) and available now via our most recent 2.0 Beta release. Now you can use both structured and semi-structured data within the same database. No longer will you need to sacrifice ACID guarantees, accuracy, or the ability to scale in order to use multiple data models within the same database. This post will explain how we implemented JSON and give you a few examples of how JSON can be used to model your data.

\* *This blog from 2018 does not represent the most recent strategies for pinning data to locations at the row level in CockroachDB. And certain capabilities referenced, like interleaving, are no longer supported. This documentation about our multi-region capabilities is the best place to begin learning about the current best practices for scaling your database across multiple regions: https://www.cockroachlabs.com/docs/stable/multiregion-overview* ```

Andy Woods

March 15, 2018

In tech, we hear the importance of “scale” all the time. People plan for it, try to work around not having it, and build companies to help others achieve it. But when it comes time to scale something yourself or integrate a scalable solution with your app, it’s difficult to find practical guides to help you understand what it takes. Why’s that? Well, it’s kind of hard. Actually scaling a database beyond a single availability zone takes considerable planning and engineering investment––but that being said, it’s an incredibly powerful tool to delight your users with low latencies and high availability.

The Baidu DBA team has been an active part of our community for quite some time. Starting in 2015 as open source contributors, they became internal evangelists of CockroachDB, ultimately building several production applications. Late last year, the team approached us with an exciting proposition. They wanted to take part in leading, building, and growing the CockroachDB open source community. Given the rapid growth and excitement surrounding CockroachDB in China, Baidu and Cockroach Labs jointly decided to hold a conference that would bring top-tier DBAs and developers together to discuss CockroachDB.

Today, we’re providing an automated way to setup multi-node CockroachDB clusters so developers can easily try out the latest stable and pre-release functionality. To automate test cluster deployment, we combine AWS CloudFormation (Amazon’s infrastructure automation product) with Kubernetes to let users spin up self-healing, horizontally scaling test clusters with just a couple clicks.

Nate Stewart

January 11, 2018

As we wrap up 2017, we would like to thank everyone who has contributed to and used CockroachDB and who has supported and encouraged all of us here at Cockroach Labs. This has been a great year for the product's - and company’s - evolution as we launched 1.0 then our 1.1, and are now well on our way to CockroachDB 2.0!

Internet of Things (IoT) and microservices-style applications need a database that can handle requirements such as fluctuating number of client connections, unpredictable workloads, and bursty throughputs. Traditional single-node databases handle these requirements by reducing latency to improve throughput. However, for modern distributed databases such as CockroachDB, the optimal approach to handle these requirements is to use multi-row SQL Data Manipulation Language (DML) and parallel processing. Multi-row DMLs provide an order-of-magnitude improvement in throughput performance as compared with equivalent single-row DMLs, which is why databases such as Oracle, MySQL, and Postgres widely support multi-row DMLs. CockroachDB has supported multi-row DMLs since the 1.0. This blog post discusses how to use multi-row DMLs, the performance benefits of multi-row DMLs over single-row DMLs, and the effects of compounding database and application parallelism in single-node vs. distributed databases.