Apache Cassandra - A NoSQL Database
Apache Cassandra® is the only distributed NoSQL database that delivers the always-on availability, blisteringly fast read-write performance, and unlimited linear scalability needed to meet the demands of successful modern applications.
What is Apache CassandraⓇ? | Open-Source Database
What is Apache Cassandra?
When downtime costs companies millions, and users expect instant access, Apache Cassandra powers the always-on, scalable applications that keep modern businesses humming. Giants like Netflix, Uber, and Apple rely on it to handle everything from streaming data to ride-tracking systems—proof it’s built for today’s modern applications.
Born at Facebook to tackle massive data challenges, it became an open-source project in July 2008. Today, it’s a distributed NoSQL database that delivers what developers need: Zero downtime, blazing performance, and the ability to grow without breaking a sweat.
Cassandra shines by managing petabytes of data and thousands of operations per second across hybrid cloud and multi-cloud setups. It simplifies operations with seamless replication across data centers and geographies. For developers and teams, that means less hassle and more focus on building—whether it’s real-time analytics or globally distributed systems. Curious how it stacks up? Let’s break it down.
Apache Cassandra vs. traditional relational databases
Choosing the right database can make or break your application’s success. Cassandra’s edge lies in its distributed design—built for speed, scale, and reliability—while traditional relational databases lean on centralized control. Here’s how they compare, and why it matters for your next project:
| APACHE CASSANDRA | RELATIONAL DATABASE |
|---|---|
| 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 |
| Decentralized deployments | Centralized deployments |
| 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 started at Facebook, built to tame the social giant’s data flood with a scalable, fault-tolerant edge. Its decentralized design was a winner from day one. Then, in 2008, Facebook flipped the script—releasing it as open source under the Apache License. That move sparked a revolution, letting companies everywhere tap into its power and pitch in to make it better.
By 2009, it hit the Apache Incubator, drawing a crowd of developers who supercharged its growth. Just a year later, in 2010, Cassandra earned top-level Apache status, cementing its rep as a go-to database. Open source didn’t just share the code—it unleashed a global collaboration that turned a Facebook fix into a modern app must-have. Check out our Apache Cassandra timeline infographic for the full scoop.
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:
- Drives innovation with open source: Forget pricey proprietary systems. Apache Cassandra lets e-commerce giants like eBay build custom solutions fast and affordably. Its open-source flexibility kills vendor lock-in, speeding up rollouts—like cutting deployment time by 30% for a retailer’s inventory system. Need enterprise-grade support? Check out DataStax Luna for peace of mind with open-source power.
- Speeds coding with a familiar interface: Cassandra Query Language (CQL) mirrors SQL, so developers at a logistics firm can query shipment data in days, not weeks. This slashes onboarding time—think a 20% faster ramp-up for teams building tracking apps—making it a go-to for rapid prototyping.
- Powers fast decisions with high performance: Unlike traditional databases bottlenecked by a single primary node, Cassandra’s every-node action handles millions of reads and writes. Streaming services like Spotify use it to process user playlists in real time, cutting latency by 40% and keeping costs low—no expensive hardware needed.
- Keeps revenue flowing with zero downtime: Cassandra ensures apps stay live during outages—think banks processing transactions or Netflix streaming without a hiccup. If a node crashes, it reroutes instantly, saving a financial firm from losing $50K per downtime hour. Built-in repairs fix issues on the fly, no babysitting required.
- Scales effortlessly for growth: Add nodes to handle spikes—like a gaming company doubling capacity for a viral launch, from 200K to 400K transactions per second overnight. Cassandra’s horizontal scaling beats vertical upgrades, saving a social platform 25% on hardware costs while keeping performance tight.
- Syncs global teams with seamless replication: Spread data across hybrid cloud setups without a hitch—perfect for a retailer syncing stock across continents. No single failure point means a travel app stays online everywhere, boosting uptime by 15% and keeping customers booking.
Understanding Cassandra's Query Language (CQL)
Cassandra has its own query language, Cassandra Query Language (CQL). It's a declarative language for communicating with Cassandra—developers use CQL commands to write and read data from the database.
CQL's simple API provides an abstraction layer that keeps Cassandra's internal storage structure and implementation details hidden. Native syntaxes for collections and other common encodings are also included.
Developers can interact with Cassandra using the CQL shell interface, cqlsh, on the command line of a node. The cqlsh prompt can be used to create and modify keyspaces and tables, make changes to data, insert and query tables, and more.
If you prefer a command line tool and use Astra DB, definitely take a look at the Astra CLI. It will install and configure CQLSH for you to work with your cloud-managed database service instance. You can also use it to manage, operate and configure your Astra DB instance via scripts or commands in a terminal.
If you prefer a graphical tool, DataStax Studio is for you. And language drivers are available for Java (JDBC), Python (DBAPI2), Node.JS (DataStax), Go (gocql), and C++. Take a look at all the drivers DataStax provides that allow CQL statements to be passed from client to cluster and back.
Comparing CQL vs SQL
New to CQL? If you know SQL, you’ll pick it up fast—think days, not weeks. CQL uses familiar tables, rows, and columns, so commands like SELECT or INSERT feel like home. A retailer can query stock levels in a snap, just like with SQL. But CQL has quirks: WHERE clauses stick to primary key columns, and every query needs a partition key. That’s the trade-off for Apache Cassandra’s speed and scale. Dig deeper into SQL vs. CQL differences here.
CQL’s data types keep it flexible—text and varchar handle strings (like customer names), integers and decimals crunch numbers (sales totals), and timestamps track orders. Need locations? Geo-spatial types map delivery routes. Collections bundle small lists like product tags, while blob, boolean, and counter types tackle niche jobs.
Want to learn more? Explore CQL data types, test-drive CQL with a quick demo, or grab our CQL Quick Reference Guide.
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 and 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:
- Full ACID transactions (CEP)
- Storage Attached Indexing (CEP)
- Making the storage engine pluggable
- Providing API compatibility for Dynamo DB with Stargate
How can I get started?
Ready to learn more about Apache Cassandra? Check out these resources to get started:
FAQs
1. What is Apache Cassandra, and how does it differ from traditional relational databases?
Apache Cassandra is a distributed NoSQL database designed for high availability, fault tolerance, and linear scalability. Unlike relational databases, which use a master node and fixed schema, Cassandra’s peer-to-peer system ensures no single point of failure. It supports efficient data distribution across multiple nodes and multiple data centers, making it ideal for distributed systems.
2. How does Apache Cassandra prevent data loss and ensure availability?
Cassandra’s replication strategy stores multiple replicas of the same data across a Cassandra cluster. The replication factor determines redundancy, reducing the risk of data loss. It also logs every write operation in a commit log for data integrity. This makes Cassandra ideal for high availability applications like logistics and asset management and authentication and fraud detection.
3. What is Cassandra Query Language (CQL), and how does it compare to SQL?
Cassandra Query Language (CQL) is similar to SQL but optimized for distributed NoSQL databases. Unlike SQL databases, which rely on relational data models, CQL supports schema flexibility, partition keys, and eventual consistency. It efficiently manages data replication, sorted string tables (SSTables), and easy data distribution across commodity servers.
4. How does Cassandra distribute and replicate data across multiple nodes?
Cassandra’s distributed architecture uses a hash function to distribute data based on the partition key, ensuring efficient data distribution across multiple data centers. The coordinator node routes queries to the appropriate Cassandra node, while multiple replicas ensure fault tolerance and data availability without a single point of failure.
5. Why choose Apache Cassandra for large-scale distributed environments?
Cassandra provides horizontal scalability, tunable consistency levels, and continuous availability for distributed database systems. It supports high availability, data security, and replicating data across multiple nodes. Ideal for inbox search features, distributed NoSQL databases, and real-time applications, Cassandra’s optimal performance outshines traditional databases. Ready to experience this at scale? Sign up for Astra DB and start building with the power of Cassandra—no infrastructure to manage.
