About Apache Cassandra 

Documentation for developers and administrators on installing, configuring, and using the features and capabilities of Apache Cassandra scalable open source NoSQL database.

DataStax no longer provides the DataStax Community version of Apache Cassandra™ or the DataStax Distribution of Apache Cassandra. See DataStax support for Apache Cassandra.
To download and install the latest version of open-source Cassandra, see https://cassandra.apache.org/.

About this document 

Welcome to the Cassandra documentation provided by DataStax. To ensure that you get the best experience in using this document, take a moment to look at the Tips for using DataStax documentation.

The landing pages provide information about supported platforms, product compatibility, planning and testing cluster deployments, recommended production settings, troubleshooting, third-party software, resources for additional information, administrator and developer topics, and earlier documentation.

Overview of Apache Cassandra 

Apache Cassandra™ is a massively scalable open source NoSQL database. Cassandra is perfect for managing large amounts of structured, semi-structured, and unstructured data across multiple datacenters and the cloud. Cassandra delivers continuous availability, linear scalability, and operational simplicity across many commodity servers with no single point of failure, along with a powerful dynamic data model designed for maximum flexibility and fast response times.

The latest version of Apache Cassandra 3.0 is 3.0.9.

How does Cassandra work? 

Cassandra’s built-for-scale architecture means that it is capable of handling petabytes of information and thousands of concurrent users/operations per second.

Cassandra is a partitioned row store database

Cassandra's architecture allows any authorized user to connect to any node in any datacenter and access data using the CQL language. For ease of use, CQL uses a similar syntax to SQL. The most basic way to interact with Cassandra is using the CQL shell, cqlsh. Using cqlsh, you can create keyspaces and tables, insert and query tables, plus much more. This Cassandra release works with CQL for Cassandra 2.2 and later. If you prefer a graphical tool, you can use DataStax DevCenter. For production, DataStax supplies a number drivers so that CQL statements can be passed from client to cluster and back.

Automatic data distribution

Cassandra provides automatic data distribution across all nodes that participate in a ring or database cluster. There is nothing programmatic that a developer or administrator needs to do or code to distribute data across a cluster because data is transparently partitioned across all nodes in a cluster.

Built-in and customizable replication

Cassandra also provides built-in and customizable replication, which stores redundant copies of data across nodes that participate in a Cassandra ring. This means that if any node in a cluster goes down, one or more copies of that node’s data is available on other machines in the cluster. Replication can be configured to work across one datacenter, many datacenters, and multiple cloud availability zones.

Cassandra supplies linear scalability

Cassandra supplies linear scalability, meaning that capacity may be easily added simply by adding new nodes online. For example, if 2 nodes can handle 100,000 transactions per second, 4 nodes will support 200,000 transactions/sec and 8 nodes will tackle 400,000 transactions/sec:


How is Cassandra different from relational databases? 

Cassandra is designed from the ground up as a distributed database with peer-to-peer communication. As a best practice, queries should be one per table. Data is denormalized to make this possible. For this reason, the concept of JOINs between tables does not exist, although client-side joins can be used in applications.

What is NoSQL? 

Most common translation is "Not only SQL", meaning a database that uses a method of storage different from a relational, or SQL, database. There are many different types of NoSQL databases, so a direct comparison of even the most used types is not useful. Database administrators today must be polyglot-friendly, meaning they must know how to work with many different RDBMS and NoSQL databases.

What is CQL? 

Cassandra Query Language (CQL) is the primary interface into the Cassandra DBMS. Using CQL is similar to using SQL (Structured Query Language). CQL and SQL share the same abstract idea of a table constructed of columns and rows. The main difference from SQL is that Cassandra does not support joins or subqueries. Instead, Cassandra emphasizes denormalization through CQL features like collections and clustering specified at the schema level.

CQL is the recommended way to interact with Cassandra. Performance and the simplicity of reading and using CQL is an advantage of modern Cassandra over older Cassandra APIs.

The CQL documentation contains a data modeling topic, examples, and command reference.

How do I interact with Cassandra? 

The most basic way to interact with Cassandra is using the CQL shell, cqlsh. Using cqlsh, you can create keyspaces and tables, insert and query tables, plus much more. If you prefer a graphical tool, you can use DevCenter. For production, DataStax supplies a number of drivers in various programming languages, so that CQL statements can be passed from client to cluster and back.

How can I move data to/from Cassandra? 

Data is inserted using the CQL INSERT command, the CQL COPY command and CSV files, or sstableloader. But in reality, you need to consider how your client application will query the tables, and do data modeling first. The paradigm shift between relational and NoSQL means that a straight move of data from an RDBMS database to Cassandra will be doomed to failure.

What other tools come with Cassandra? 

Cassandra automatically installs nodetool, a useful command-line management tool for Cassandra. A tool for load-stressing and basic benchmarking, cassandra-stress, is also installed by default.

What kind of hardware/cloud environment do I need to run Cassandra? 

Cassandra is designed to run on commodity hardware with common specifications. In the cloud, Cassandra is adapted for most common offerings.