At Cockroach Labs, we're focused on making data easy for our customers. CockroachDB is designed as a vendor-agnostic, cloud-native database for transactional workloads. We offer a number of benefits over traditional relational databases including serializable isolation, online schema changes, and high availability fault-tolerance. Today, we want to demonstrate another CockroachDB differentiator: multi-region support for global scale. In this blog post, we introduce Follower reads, a key feature for supporting multi-region reads with low latency when your use case can accept stale data.

Andy Woods

December 3, 2019

CockroachDB is a cloud-neutral database, which means it eliminates dependencies on a particular cloud environment and gives you the flexibility and choice to run it anywhere you like. We are committed to this principle and in order to deliver on this promise, we systematically deploy and test CockroachDB clusters on the three leading US cloud providers: Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.

Andy Woods

February 7, 2019

Our customers rely on us to help them navigate the complexities of the increasingly competitive cloud wars. Should they use Amazon Web Services (AWS)? Google Cloud Platform (GCP)? Microsoft Azure? How should they tune their workload for different offerings? Which is more reliable?

Andy Woods

December 13, 2018

[For CockroachDB's most up-to-date performance benchmarks, please read our Performance Overview page] Correctness, stability, and performance are the foundations of CockroachDB. Today, we will demonstrate our rapid progress in performance and scalability with CockroachDB 2.1. CockroachDB is now 50x more scalable than Amazon Aurora at less than 2% of the price per tpmC. And unlike Aurora and other databases that selectively degrade isolation levels for performance, CockroachDB can achieve massive scale while maintaining serializable isolation, protecting your data from fraud and data loss. Read on to see benchmarked metrics that demonstrate that CockroachDB can provide customers an ultra-resilient and highly available database at massive scale.

Andy Woods

November 28, 2018

CockroachDB provides scale without sacrificing SQL functionality. It offers fully-distributed ACID transactions, zero-downtime schema changes, and support for secondary indexes and foreign keys. But what about some of the additional benefits NoSQL databases provide such as the ability to use semi-structured data? CockroachDB listened to our customers and realized that we needed to provide options for managing rapid development, data without a clear schema or whose schema you do not control, and impedance mismatches. That’s why we are excited to support JSON in 2.0! Previously we’ve shown you how we implemented JSON and inverted indexes as well as a few examples. This blog post will explain when you might want to leverage these features.

Andy Woods

June 21, 2018

The three design principles of CockroachDB are correctness, stability, and performance. Having achieved our correctness and stability goals with CockroachDB 1.0 and 1.1, we focused heavily on performance with CockroachDB 2.0. For more information on which benchmarks matter, or to see a comparison between CockroachDB 1.1 and 2.0, you can read CockroachDB 2.0 Makes Significant Strides. Today we are releasing a comprehensive whitepaper that demonstrates how CockroachDB achieves high OLTP performance of over 128,000 tpmC on a TPC-C dataset over 2 terabytes in size. This OLTP performance is over 10x more TPC-C throughput than Amazon Aurora, in a 3x replicated deployment with single-digit seconds recovery time and zero-downtime migrations and upgrades. This far surpasses a typical active-passive database deployment with manual failure recovery. CockroachDB achieves this in serializable isolation, unlike competing databases that sacrifice isolation for performance. We’re very excited to talk about performance, and have taken care to make this more than just an announcement with vague numbers. In keeping with our open source philosophy, our whitepaper contains a step-by-step reproduction of instructions to verify all our performance claims, as well as context on our benchmarking philosophy and practices. We don’t just want you to take our word for our performance numbers, we’d like to arm you with all the tools you need to check it out for yourself! In this post, we’d like to cover some brief highlights, but do check out the whitepaper for more details and a fully reproducible test script.

Andy Woods

April 18, 2018

As we’ve written about previously, geographically distributed databases like CockroachDB offer a number of benefits including reliability, security, and cost-effective deployments. We believe you shouldn’t have to sacrifice these upsides to realize impressive throughput and low latencies. That’s why we created geo-partitioning. This blog post defines two new features, geo-partitioning and archival-partitioning, as well as explains when you might want to leverage these features. We previously provided a sneak-peak walkthrough of geo-partitioning that can be found here.

Andy Woods

April 12, 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.

Andy Woods

March 22, 2018