Engineering

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

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.

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.

For the past four months, I’ve worked as a backend engineering intern with the incredibly talented engineers of the Cockroach Labs SQL Execution team to unlock the full potential of the vectorized engine ahead of the CockroachDB 20.1 release. During this time, I focused on improving the algorithm behind some of CockroachDB’s SQL operators, to reduce memory usage and speed up query execution. In this blog post, I will go over the improvements that I made to the algorithm behind the unordered distinct operator, as well as new algorithms that address some existing inefficiencies.

Late last year, we shipped v1 of our vectorized execution engine. It enables column-based query execution and speeds up complex joins and aggregations, improving analytical capabilities in CockroachDB (which is first and foremost optimized for OLTP workloads). v1 of the engine didn’t support disk spilling, which meant it couldn’t execute certain memory-intensive queries if there was not enough memory available. Starting in CockroachDB v20.1, these queries fall back to disk (also known as “spilling” to disk).

We didn’t implement SELECT FOR UPDATE to ensure consistency. Unlike Amazon Aurora, CockroachDB already guarantees serializable isolation, the highest isolation level provided by the ANSI SQL standard. Contention happens. And application developers shouldn’t need to risk the integrity of their data when transactions contend. To combat this, CockroachDB must occasionally return errors prompting applications to retry transactions that would risk anomalies, such as write skews. This means that just like with PostgreSQL in serializable isolation, developers need to implement retry-loops for contended transactions. For developers accustomed to relational databases with lower isolation levels, this can be an unfamiliar pattern.

John Kendall

June 22, 2020

CockroachDB 20.1 introduces support for nested transactions, a SQL feature which simplifies the work of programmers of certain client applications. In this post, we'll explore when and where to use nested transactions, when not to use them, and how they work in a distributed environment.

Over the past few months, a team of our engineers, technical writers, product managers, and sales engineers codified the research and learnings of CockroachDB and are now contributing this knowledge back into the very system from which we have benefited with the hope of further advancing distributed systems research and design. The research paper, "CockroachDB: The Resilient Geo-Distributed SQL Database", is a labor of love that we are honored to have published by SIGMOD, the Association for Computing Machinery's (ACM) Special Interest Group on Management of Data, which specializes in large-scale data management problems.

Jessica Edwards

June 10, 2020

As of our 20.1 release, CockroachDB supports online primary key changes. This means that it is now possible to change the primary key of a table while performing read and write operations on the table. Online primary key changes make it easier to transition an application from being single-region to multi-region, or to iterate on the schema of an application with no down time. Let’s dive into the technical challenges behind this feature, and our approach to solving them. As part of the deep dive, let’s review how data is stored in CockroachDB, and how online schema changes work in CockroachDB.