Apache Cassandra explained
Apache Cassandra is a distributed NoSQL database created at Facebook and later released as an open-source project in July 2008.
Cassandra delivers the continuous availability (zero downtime), high performance, and linear scalability that modern applications require, while also offering operational simplicity and effortless replication across multiple data centers and geographies. It can handle petabytes of information and thousands of concurrent operations per second, enabling organizations to manage large amounts of structured data across hybrid and multi-cloud environments.
Apache Cassandra vs. traditional relational databases
Cassandra differs from a typical relational database in the following ways:
|Handles high incoming data velocity
|Handles moderate incoming data velocity
|Supports simple transactions
|Supports complex/nested transactions
|No single points of failure; constant uptime
|Single points of failure with failover
|Supports very high data volumes
|Supports moderate data volumes
|Data written in many locations
|Data written in mostly one location
|Supports read and write scalability
|Supports read scalability (with consistency sacrifices)
|Deployed in horizontal scale-out fashion
|Deployed in vertical scale-up fashion
Please check out our NoSQL primer, if you'd like to learn more about how Cassandra and other NoSQL databases compare to relational databases.
History of Apache Cassandra
Apache Cassandra’s key features and benefits
Whether you need to process server logs, emails, social media posts, or PDFs, Cassandra has you covered. You’ll be able to make better-informed decisions without leaving any of your data on the table.
Here are some of Cassandra's key benefits and features:
Open source: Modern software development organizations have overwhelmingly moved to adopt open-source technologies, starting with the Linux operating system and progressing to infrastructure for managing data. Open-source technologies are attractive because of their affordability and extensibility, as well as the flexibility to avoid vendor lock-in. Organizations adopting open source report higher speed of innovation and faster adoption.
Flexible, familiar interface: The Cassandra Query Language (CQL) is similar to SQL. That means most developers should have a fairly easy time becoming familiar with it. Learn more about CQL below.
High performance: The majority of traditional relational databases feature a primary / secondary architecture. In these configurations, a single primary replica performs read and write operations, while secondary replicas are only able to perform read operations. Downsides to this architecture include increased latency, higher costs, and lower availability at scale. With Cassandra, no single node is in charge of replicating data across a cluster. Instead, every node is capable of performing all read and write operations. This improves performance and adds resiliency to the database.
Active everywhere with zero downtime: Since every Cassandra node is capable of performing read and write operations, data is quickly replicated across hybrid cloud environments and geographies. If a node fails, users will be automatically routed to the nearest healthy node, leaving no single point of failure. They won’t even notice that a node has been knocked offline because applications behave as designed even in the event of failure. As a result, applications are always available and data is always accessible and never lost. What’s more, Cassandra’s built-in repair services fix problems immediately when they occur—without any manual intervention. Productivity doesn’t need to take a hit if nodes fail.
Scalability: In traditional environments, scaling applications is a time-consuming and costly process typically accomplished by scaling vertically with more expensive machines. Cassandra enables you to scale horizontally by simply adding more nodes to the cluster. If, for example, four nodes can handle 200,000 transactions/second, eight nodes will be able to handle 400,000 transactions/second.
Seamless replication: Today’s leading enterprises are increasingly moving to multi-data center, hybrid cloud, and even multi-cloud deployments to take advantage of the strengths of each, without getting locked into any single provider’s ecosystem. By placing data on different machines, it proves easy data distribution with no single point of failure. Getting the most out of multi-cloud environments, however, starts with having an underlying cloud database that offers scalability, security, performance, and availability. For these reasons, it should come as no surprise that the cloud database market is expected to grow nearly 65% each year and reach $68.9 billion by 2022.
Understanding Cassandra’s Query Language (CQL)
Where is Apache Cassandra headed next?
At DataStax, we’re working hard with the open-source community to build on Cassandra’s decade-plus maturity to solidify its position as the leading database for cloud-native applications.
Cassandra has traditionally been known as an extremely powerful database that stands up to the most demanding use cases, but also as difficult to learn and operate. DataStax is committed to working with the Cassandra community to make it easier to use, adopt, and extend for your needs.
Here are some of the ideas we’re exploring:
Enhancing the JSON Document API for Cassandra in Stargate
Expanding Postman collections and community
Enabling ecosystem extension for new data APIs
Adding more SQL-like capabilities into CQL:
How can I get started?
If you’d like to learn more about Apache Cassandra, we have several resources here to get you started.
DataStax for Developers
Learn how to succeed with Apache Cassandra™.
Try DataStax Astra DB
Rapidly build cloud-native applications with DataStax Astra DB, a database-as-a-service built on Apache Cassandra.
Apache Cassandra 4.0 White Paper
Get your free digital copy to harness Cassandra 4.0's performance and reliability