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Today marks the 99th anniversary of the birth of Edgar F. Codd, the author of “A Relational Model of Data for Large Shared Data Banks” and godfather of the relational database. Ted Codd did for the database what Xerox PARC did for personal computers: made them accessible to everyday humans. Long before the invention of computers, there were databases. As early as 2400 BC the ancient Sumerians were carving tablets recording medical prescriptions for different ailments. Lists of Roman citizens on parchment scrolls. Card catalogs. Rolodexes. Even after computers were invented, data was far from automated. Early database models used a “flat file” system – a simple consecutive list of records that required the computer to begin at the start of the list and search sequentially. A very slow way to search, add to, and maintain large volumes of records. Meanwhile, we had a moon to get to! Humanity needed a way to access and interact with data in a fast, efficient, and accurate way.

Michelle Gienow

August 19, 2020

As a startup, our policies and processes constantly evolve. All content in this post is true at the time of publication. For the most up-to-date information, please visit our careers page or reach out to recruiting@cockroachlabs.com Adjusting to a completely remote lifestyle to weather a pandemic has been no easy feat. For many of us, maintaining productivity has been even harder. Cockroach Labs is working hard to ensure that our people have what they need to take care of themselves and work effectively, no matter where they are. Our company was founded with a belief in establishing balance and flexibility at the core of our organizational philosophy. We say so proudly on our careers website: “We care about productivity, not face time.” This principle has driven how we put best practices in place surrounding remote work, asynchronous communication, and relocating throughout your career with us. We’re particularly proud of how this commitment has smoothed the quick transition to company-wide remote work at the height of COVID-19’s spread. Our foremost goal at the start of the pandemic was (and remains) to make sure that our team is safe and practicing vital social distancing measures. From our founding in 2015, most of our early team was based in New York City. Over time, as we began to hire Roachers in metro regions throughout the US, we spun up co-working spaces in those new cities. Later, we did the same in Toronto to bring our past interns from Canada on board! Opening these offices meant welcoming more talent from more parts of the world and we’re happy to do so. As we’ve expanded our sales team, we’ve started hiring for revenue roles in the UK, too. We will continue to evaluate new regions as we grow, but we’ve confirmed an important hypothesis: a scaling workforce can still build the world’s best distributed database.

From our enterprise customers to developer shops, a lot of folks use CockroachDB to back their Spring applications. It’s no surprise; Java is the most widely used programming language in the world, running in over 3 billion devices. And no matter what kind of application you’re running, the Spring ecosystem provides different data access patterns depending on your needs. We’ve recently added tutorials for a number of Spring data access patterns: Spring Data JDBC, Spring Data JPA, and MyBatis. Check them out below.

Meagan Goldman

August 10, 2020

This past February, before the pandemic was deemed a pandemic and New York City was still humming along, as usual, I sat down at Cockroach Labs HQ to talk about the future of data in application development. It’s a broad topic and one that’s about to undergo a fundamental and immutable shift. We’ll get to why in just a minute.

Spencer Kimball

August 3, 2020

One of the great things about CockroachDB’s support for SQL is the ecosystem of frameworks, ORMs, and other tools for working with SQL data. SQLAlchemy is just one of the ORMs in that ecosystem, and one we use quite a bit for Python projects. You’ll find it referenced in some of our sample application docs, and our upcoming “CockroachDB for Python Developers” course has students use SQLAlchemy and Flask in projects.

Meagan Goldman

July 28, 2020

Gartner predicts that by 2022, 75% of all databases will be deployed in the cloud. The findings shouldn’t come as a surprise: on-premise data centers are slowly being phased out as companies realize the many benefits to running a database in the cloud.

As organizations migrate to the cloud, they need a cloud-native, relational database to help them move all their applications to this new environment. Over the last ten years, the infrastructure that runs our applications has fundamentally changed. As we move to the cloud, we now have to think about managing workloads in an environment where we don’t have tight control over the infrastructure that hosts our applications. Things like “how can I recover my data?” and “what happens if my instance fails?” are very different when you host applications in the cloud. And we’re doing it at a scale that was once only considered by a handful of companies worldwide. Largely, these changes have been positive. Launching a new technology no longer requires months of planning, procuring, and commissioning hardware. Our individual apps have become a combination of micro-services that work together and can be set up to scale dynamically as traffic demands. We can try out something new without having to convince management that it’s worth a capital investment. However, when it comes to data, it hasn’t been easy to make the transition.

Keith McClellan

July 17, 2020

CockroachDB’s 20.1 release supports lateral joins, which can dramatically reduce the lines of code needed to arrive at key business analytics. Today, I’m going to walk you through a demo of lateral joins and showcase how you might use them to run analytic queries directly in CockroachDB.

Andy Woods

July 16, 2020

In 2018, CockroachDB implemented a cost-based query optimizer from scratch, which has been steadily improved in each release. The query optimizer is the part of the system that understands the semantics of SQL queries and decides how to execute them; execution plans can vary wildly in terms of execution time, so choosing a good plan is important. In this post we go over some of the optimizer-related improvements in CockroachDB v20.1.