Cassandra

Apache Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. It uses a decentralized, peer-to-peer architecture with a masterless design, making it fault-tolerant and suitable for mission-critical applications. Cassandra's data model is based on a wide-column store, offering flexible schema design and efficient read/write operations for time-series, IoT, and real-time analytics workloads.

Also known as: Apache Cassandra, CassandraDB, Cassandra Database, Cassandra NoSQL, Cassandra DB
🧊Why learn Cassandra?

Developers should learn Cassandra when building applications that require massive scalability, high write throughput, and low-latency reads across geographically distributed data centers, such as in e-commerce, social media, or IoT platforms. It is particularly useful for use cases involving time-series data, event logging, and real-time analytics where traditional relational databases struggle with performance under heavy loads. Cassandra's tunable consistency and partition tolerance make it ideal for CAP theorem scenarios where availability and partition tolerance are prioritized over strong consistency.

See how it ranks →

Compare Cassandra

Learning Resources

Related Tools

Alternatives to Cassandra

Other Column Databases

View all →
Always On Availability Groups
Always On Availability Groups is a high-availability and disaster recovery solution in Microsoft SQL Server that provides database-level failover for groups of databases. It allows multiple copies of a set of databases (availability replicas) to be maintained across different servers, ensuring data redundancy and automatic failover in case of primary server failure. This feature supports both synchronous and asynchronous data replication modes to balance performance and data protection needs.
Amazon Aurora
Amazon Aurora is a fully managed, MySQL and PostgreSQL-compatible relational database service built for the cloud. It combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases, offering up to five times the throughput of standard MySQL and three times that of PostgreSQL. Aurora automatically handles tasks like hardware provisioning, database setup, patching, backups, and replication, while providing high durability and availability through distributed, fault-tolerant, self-healing storage.
Amazon Aurora Provisioned
Amazon Aurora Provisioned is a fully managed relational database service from AWS that offers high performance, scalability, and availability with MySQL and PostgreSQL compatibility. It uses a distributed, fault-tolerant storage system that automatically scales up to 128 TB per database instance, providing fast read replicas and continuous backup to Amazon S3. This provisioned model requires users to pre-allocate and pay for database instance capacity, making it suitable for predictable workloads.
Amazon Aurora Serverless
Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora, a MySQL and PostgreSQL-compatible relational database built for the cloud. It automatically starts up, shuts down, and scales capacity up or down based on application demand, eliminating the need to manage database instances. This serverless model is designed for applications with intermittent, unpredictable, or variable workloads.
Amazon Aurora Serverless
Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora, a MySQL and PostgreSQL-compatible relational database built for the cloud. It automatically starts up, shuts down, and scales capacity up or down based on application demand, eliminating the need to manage database instances. This serverless model is designed for applications with intermittent, unpredictable, or variable workloads.
Amazon DynamoDB
Amazon DynamoDB is a fully managed NoSQL database service provided by Amazon Web Services (AWS) that offers fast and predictable performance with seamless scalability. It supports key-value and document data models, automatically replicates data across multiple Availability Zones for high availability and durability, and provides built-in security, backup, and in-memory caching capabilities.