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This post was originally published in 2017, upon announcing that CockroachDB’s support for Hibernate was in beta. Today, we’re excited to announce some big news: the CockroachDB dialect for Hibernate is officially available! 🥳 Hibernate now offers first-class support for CockroachDB. You can read more about the dialect, and our journey to get there, in this blog post.

Since its inception, CockroachDB has relied on RocksDB as its key-value storage engine. The choice of RocksDB has served us well. RocksDB is battle tested, highly performant, and comes with a rich feature set. We’re big fans of RocksDB and we frequently sing its praises when asked why we didn’t choose another storage engine. Today we’re introducing Pebble.

Peter Mattis

September 15, 2020

The first version of CockroachDB Dedicated, our database-as-a-service product, had our users fill out a Google doc with their cloud deployment preferences. We’ve come a long way since that initial proof of concept (including, yes, building a UI). More importantly, we’ve put implementation patterns in place that make something complicated (like configuring a cloud deployment) scalable. As we’ve written about before, choosing to run CockroachDB Dedicated on Kubernetes is a huge part of that implementation pattern.

Databases are evolving. For the past decade, we’ve read thinkpiece after thinkpiece taking firm stances on the “SQL vs. NoSQL” debate--some of which declaratively pronounce the death of SQL or the death of NoSQL. In DZone’s annual report on SQL v NoSQL database usage, we’re excited to see that we’re moving beyond that paradigm. What we’re seeing in this report is more nuanced, and a lot more exciting: the death of the “SQL vs. NoSQL” binary altogether.

The other week, we devoted an episode of The Cockroach Hour to talk about the dirty secret of isolation levels. When host Jim Walker was titling the webinar, I’m pretty sure he had one particular “secret” in mind: dirty reads. But the conversation kicked off with discussion of an even more pervasive secret: most developers don’t pay attention to isolation levels. Guests Tim Veil and John Sheaffer, both Solutions Engineers at Cockroach Labs, have decades of experience developing against and working with–and for–all sorts of databases. And both of them admitted that for years, they weren’t paying enough attention to what was happening with their applications' consistency models and isolation levels.

In this post, I’ll skim the surface of a very common pattern in application development: full text indexing and search. I’ll start with a bit of motivation, what prompted me to explore this using CockroachDB. Next, I’ll introduce the initial pass at a solution, followed by a deeper explanation of how that was done, and I’ll then improve on that result by adding a “score”. Finally, I’ll discuss the limitations of this simplistic approach, within the context of information retrieval, ending with my answer to “So, why’d you do it?” Let’s get started.

Michael Goddard

August 27, 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.

There are many reasons you might want to alter the schema of your database but in many databases, this process typically requires downtime. In CockroachDB, we have supported online schema changes since our first stable release, and in v20.1, we added the ability to alter primary keys while in production without downtime.

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