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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.

Geographically distributed databases like CockroachDB offer a number of benefits including reliability, security, cost-effective deployments, and more. Critics often counter that distributed databases increase latency. What if a database could offer all of the benefits of distribution, but also provide low-latency? With this challenge in mind, we set out to minimize latency in CockroachDB, all the while providing exceptional reliability for mission-critical workloads. We built “follow-the-workload” to be a key feature to improve performance and provide additional control to database administrators (DBAs).

Andy Woods

December 5, 2017

Geographically distributed databases like CockroachDB offer a number of benefits including reliability, cost-effective deployments, and more. Critics often counter that distributed databases increase latency. What if a database could offer all of the benefits of distribution, but also provide low latency?

Andy Woods

November 30, 2017

Since the U.S. Equal Employment Opportunity Commission (EEOC) opened their doors for business on July 2, 1965, a year after Title VII’s enactment into law, the mission to eliminate unlawful employment discrimination has made progress in our society. No one can deny that we are in a significantly better place than we were just over 50 years ago. The act has benefited many and has served as a model for future anti-discrimination measures passed by Congress, including the Pregnancy Discrimination Act and the Americans with Disabilities. However, the passing of this legislation has by no means solved the problem of discrimination in the workplace. Discrimination is not as overt, but is rather found in grey areas, lurking beneath the surface and often rooted deep into an individual’s unconscious bias. I know what you are thinking: “I know I have biases, but I don’t discriminate against people who are different from me!” It feels shameful. Your biases are shaped by your experiences, culture, and your lifestyle. They frame your perspective and the way you behave in the world. It’s not shameful. However, we believe that recognizing your bias and how it affects your decision-making processes will allow you to understand if and how those biases are impeding your organization's ability to create a balanced and inclusive workforce. At Cockroach Labs, we have put processes in place for our employees to be aware of the role their unconscious bias plays in hiring decisions they are making. We have removed the dependency on resumes and focused on exercise based interviewing. Our end goal is to create practices that lead to a more inclusive culture. It’s proven that by providing candidates with an understanding of what to expect throughout the process, as well as insight into what to expect, helps them perceive the process as being fair [Klehe, König, Richter, Kleinmann, Melchers]. In addition to creating fairness, we want to see if full transparency can also lead to better hiring outcomes. With this in mind, we have made the decision to open source our interview process.

Lindsay Grenawalt

November 28, 2017

For the first two years of CockroachDB’s existence, the Windows installation instructions read like this: Install Docker. Get the latest CockroachDB Docker image: docker pull cockroachdb/cockroach The instructions were deceptively short, considering that they amounted to downloading a supported operating system (Linux), booting it in a hypervisor, and running CockroachDB inside of that virtual machine.