- What is CockroachDB?
- Docs
- Quickstart
- Client Drivers
- Deployment
- Get In Touch
- Contributing
- Tech Talks
- Design
CockroachDB is a distributed SQL database built on a transactional and strongly-consistent key-value store. It scales horizontally; survives disk, machine, rack, and even datacenter failures with minimal latency disruption and no manual intervention; supports strongly-consistent ACID transactions; and provides a familiar SQL API for structuring, manipulating, and querying data.
For more details, see our FAQ and original design document.
CockroachDB is currently in beta. See our Roadmap and Issues for a list of features planned or in development.
For guidance on installation, development, deployment, and administration, see our User Documentation.
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Start a local cluster with three nodes listening on different ports:
$ ./cockroach start --background $ ./cockroach start --store=cockroach-data2 --port=26258 --http-port=8081 --join=localhost:26257 --background $ ./cockroach start --store=cockroach-data3 --port=26259 --http-port=8082 --join=localhost:26257 --background
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Start the built-in SQL client as an interactive shell:
$ ./cockroach sql # Welcome to the cockroach SQL interface. # All statements must be terminated by a semicolon. # To exit: CTRL + D.
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Run some CockroachDB SQL statements:
root@:26257> CREATE DATABASE bank; CREATE DATABASE root@:26257> SET DATABASE = bank; SET root@:26257> CREATE TABLE accounts (id INT PRIMARY KEY, balance DECIMAL); CREATE TABLE root@26257> INSERT INTO accounts VALUES (1234, DECIMAL '10000.50'); INSERT 1 root@26257> SELECT * FROM accounts; +------+----------+ | id | balance | +------+----------+ | 1234 | 10000.50 | +------+----------+
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Checkout the admin UI by pointing your browser to
http://<localhost>:8080
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CockroachDB makes it easy to secure a cluster.
CockroachDB supports the PostgreSQL wire protocol, so you can use any available PostgreSQL client drivers to connect from various languages. For recommended drivers that we've tested, see Install Client Drivers.
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Manual - Steps to deploy a CockroachDB cluster manually on multiple machines.
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Cloud - Configuration files and instructions for deploying an insecure development or test cluster on GCE or AWS using Terraform.
When you see a bug or have improvements to suggest, please open an issue.
For development-related questions and anything else, there are two easy ways to get in touch:
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Join us on Gitter - This is the best, most immediate way to connect with CockroachDB engineers.
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Post to our Developer mailing list - Please join first or you messages may be held back for moderation.
We're an open source project and welcome contributions.
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See CONTRIBUTING.md to get your local environment set up.
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Take a look at our open issues, in particular those with the helpwanted label.
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Review our style guide and follow our code reviews to learn about our style and conventions.
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Make your changes according to our code review workflow.
For recordings and slides from talks given by CockroachDB founders and engineers, see Tech Talks.
This is an overview. For an in-depth discussion of the design and architecture, see the full design doc. For another quick design overview, see the CockroachDB tech talk slides.
CockroachDB is a distributed SQL database built on top of a transactional and consistent key:value store. The primary design goals are support for ACID transactions, horizontal scalability and survivability, hence the name. CockroachDB implements a Raft consensus algorithm for consistency. It aims to tolerate disk, machine, rack, and even datacenter failures with minimal latency disruption and no manual intervention. CockroachDB nodes (RoachNodes) are symmetric; a design goal is homogeneous deployment (one binary) with minimal configuration.
CockroachDB implements a single, monolithic sorted map from key to value
where both keys and values are byte strings (not unicode). CockroachDB
scales linearly (theoretically up to 4 exabytes (4E) of logical
data). The map is composed of one or more ranges and each range is
backed by data stored in RocksDB (a variant of LevelDB), and is
replicated to a total of three or more CockroachDB servers. Ranges are
defined by start and end keys. Ranges are merged and split to maintain
total byte size within a globally configurable min/max size
interval. Range sizes default to target 64M in order to facilitate
quick splits and merges and to distribute load at hotspots within a
key range. Range replicas are intended to be located in disparate
datacenters for survivability (e.g. { US-East, US-West, Japan }
, { Ireland, US-East, US-West}
, { Ireland, US-East, US-West, Japan, Australia }
).
Single mutations to ranges are mediated via an instance of a distributed consensus algorithm to ensure consistency. We’ve chosen to use the Raft consensus algorithm. All consensus state is stored in RocksDB.
A single logical mutation may affect multiple key/value pairs. Logical mutations have ACID transactional semantics. If all keys affected by a logical mutation fall within the same range, atomicity and consistency are guaranteed by Raft; this is the fast commit path. Otherwise, a non-locking distributed commit protocol is employed between affected ranges.
CockroachDB provides snapshot isolation (SI) and serializable snapshot isolation (SSI) semantics, allowing externally consistent, lock-free reads and writes--both from an historical snapshot timestamp and from the current wall clock time. SI provides lock-free reads and writes but still allows write skew. SSI eliminates write skew, but introduces a performance hit in the case of a contentious system. SSI is the default isolation; clients must consciously decide to trade correctness for performance. CockroachDB implements a limited form of linearalizability, providing ordering for any observer or chain of observers.
Similar to Spanner directories, CockroachDB allows configuration of arbitrary zones of data. This allows replication factor, storage device type, and/or datacenter location to be chosen to optimize performance and/or availability. Unlike Spanner, zones are monolithic and don’t allow movement of fine grained data on the level of entity groups.