Apache Cassandra

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

Free • Open Source
Relational Database
Mac
Windows
Linux
BSD
Amazon Web Services
Google Cloud Platform
Microsoft Azure

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What is Apache Cassandra?

Apache Cassandra has become the leading NoSQL platform driving many of today's modern business applications by offering continuous availability, high scalability and performance, strong security, and operational simplicity while lowering the overall cost of ownership.

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages.

Cassandra's data model offers the convenience of column indexes with the performance of log-structured updates, strong support for denormalization and materialized views, and powerful built-in caching. Data is automatically replicated to multiple nodes for fault-tolerance. Replication across multiple data centers is supported. Failed nodes can be replaced with no downtime.
Read and write throughput both increase linearly as new machines are added, with no downtime or interruption to applications.

Learn more with code samples, workshops, demos and more at https://www.datastax.com/dev
Try it out on DataStax Astra's Free Forever Tier (5GB) on AWS, Azure or Google Cloud: https://astra.datastax.com/register

Astra natively supports the http://stargate.io project, which adds automatic API endpoints for REST, schemaless, document-style JSON over REST, GraphQL (with more APIs on the way). Astra and stargate also separate coordination from storage in separate nodes, resulting in more flexible architecture and lower resource utilization when scaling.

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