Product

One small step for Cockroach Labs, one giant leap for our release numbering. Since our initial launch, Cockroach Labs has used semantic versioning in our release cycle guidelines. Two years, one major release, and n-patch fixes later, we're making the switch to Calendar Versioning. This means subscribers to our release notes will see quite the jump in today's version numbering, from last week's 2.1.5 to today's 19.1 beta.

Peter Mattis

February 25, 2019

CockroachDB was built to help teams scale their applications across the globe without sacrificing SQL’s convenience, power, and data-integrity guarantees. In CockroachDB 2.1, we’ve made it easier than ever to migrate from MySQL and Postgres, improved our scalability on transactional workloads by 5x, and launched a managed offering to help teams deploy low-latency, multi-region clusters with minimal operator overhead.

Nate Stewart

November 1, 2018

This week we’re pleased to announce the availability of Managed CockroachDB, the fully hosted and fully managed service created and run by Cockroach Labs that makes deploying, scaling, and managing CockroachDB effortless. Managed CockroachDB is cloud agnostic and available at launch on both AWS and GCP. The goal is simple: allow your development team to focus on building highly scalable applications without worrying about infrastructure operations.

Spencer Kimball

October 30, 2018

CockroachDB makes it possible to support a global customer base while remaining compliant with data privacy regulations. Operators interact with a single logical control plane that they can use to define how they want CockroachDB to store their row-level data. Meanwhile, developers continue to interact with our PostgreSQL-compatible API that transparently handles distributing queries across a global cluster. With our 2.0 release, we introduced a new cluster visualization in our web UI to help operators monitor a global cluster.

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.

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

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.