apache/cassandraPublic

Open source transactional distributed database. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure without compromising performance.

AI summary: Highly scalable, partitioned row store database designed for zero single points of failure.

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JavaApache-2.0Created May 21, 2009Last push today+19 stars this week+27 this month

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since Jan 8, 2023
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10.1K stars as of Aug 7, 2026, tracked back to Jan 8, 2023. Historical curve reconstructed from public GitHub event archives, calibrated to the current total.

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828 commits in the last yearLessMore

Signals and awards

derived from tracked data
  • Widely adopted

    10,058 stars

  • Battle-tested

    17 years of history

  • Very active

    828 commits in 52 weeks

  • Community-driven

    ~685 contributors

  • Well documented

    High community health score

  • Permissive license

    Apache-2.0

  • Continuous integration

    Automated checks passing

What cassandra does

Apache Cassandra is a distributed NoSQL database built for extreme scalability and fault tolerance across commodity hardware or cloud infrastructure. It organizes data in partitioned rows using a primary key and seamlessly replicates data across multiple datacenters. Its decentralized architecture means there is no master node, allowing nodes to be added or removed without downtime, and it provides a SQL-like interface called Cassandra Query Language (CQL) for familiar data modeling.

Data engineers, backend developers, and enterprise architects managing massive datasets requiring high availability and linear write scalability.

  • Decentralized architecture: Every node in the cluster plays an identical role, eliminating single points of failure.
  • Transparent repartitioning: Automatically redistributes data across the cluster as nodes are added or removed.
  • CQL interface: Provides a familiar SQL-like query language for defining schemas and querying data.
  • Multi-datacenter replication: Natively supports replicating data across multiple geographical regions for disaster recovery.
  • Tunable consistency: Allows developers to trade off between strong data consistency and high availability on a per-query basis.
  • Partitioned row store: Combines the flexibility of key-value stores with the structure of column families for efficient time-series data.

Where teams use it

Global time-series data

IoT platforms write millions of sensor data points per second with low latency and automatic expiration.

High-availability retail catalogs

E-commerce sites use multi-datacenter replication to ensure the product catalog remains online even if an entire region fails.

User activity tracking

Social networks store vast amounts of clickstream and telemetry data distributed across thousands of commodity servers.

Messaging infrastructure

Chat applications leverage the partitioned row store to efficiently append and retrieve massive chat histories.

Getting started: docker run -p 9042:9042 cassandra

README

trunk branch

License Build Status     Official Downloads Docker Pulls     Slack Bluesky LinkedIn Youtube

Apache Cassandra

Apache Cassandra is a highly-scalable partitioned row store. Rows are organized into tables with a required primary key.

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster.

Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

For more information, see the Apache Cassandra web site.

Issues should be reported on The Cassandra Jira.

Requirements

  • Java: see supported versions in build.xml (search for property "java.supported").

  • Python: for cqlsh, see bin/cqlsh (search for function "is_supported_version").

Getting started

This short guide will walk you through getting a basic one node cluster up and running, and demonstrate some simple reads and writes. For a more-complete guide, please see the Apache Cassandra website’s Getting Started Guide.

First, we’ll unpack our archive:

$ tar -zxvf apache-cassandra-$VERSION.tar.gz
$ cd apache-cassandra-$VERSION

After that we start the server. Running the startup script with the -f argument will cause Cassandra to remain in the foreground and log to standard out; it can be stopped with ctrl-C.

$ bin/cassandra -f

Now let’s try to read and write some data using the Cassandra Query Language:

$ bin/cqlsh

The command line client is interactive so if everything worked you should be sitting in front of a prompt:

Connected to Test Cluster at localhost:9160.
[cqlsh 6.3.0 | Cassandra 7.0-SNAPSHOT | CQL spec 3.4.8 | Native protocol v5]
Use HELP for help.
cqlsh>

As the banner says, you can use 'help;' or '?' to see what CQL has to offer, and 'quit;' or 'exit;' when you’ve had enough fun. But lets try something slightly more interesting:

cqlsh> CREATE KEYSPACE schema1
       WITH replication = { 'class' : 'SimpleStrategy', 'replication_factor' : 1 };
cqlsh> USE schema1;
cqlsh:Schema1> CREATE TABLE users (
                 user_id varchar PRIMARY KEY,
                 first varchar,
                 last varchar,
                 age int
               );
cqlsh:Schema1> INSERT INTO users (user_id, first, last, age)
               VALUES ('jsmith', 'John', 'Smith', 42);
cqlsh:Schema1> SELECT * FROM users;
 user_id | age | first | last
---------+-----+-------+-------
  jsmith |  42 |  john | smith
cqlsh:Schema1>

If your session looks similar to what’s above, congrats, your single node cluster is operational!

For more on what commands are supported by CQL, see the CQL reference. A reasonable way to think of it is as, "SQL minus joins and subqueries, plus collections."

Wondering where to go from here?

View on GitHub

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