Apache Cassandra
What it is: Distributed NoSQL database designed for massive scale. Wide-column store with no single point of failure, linear scalability.
What It Does Best
Always-on availability. Multi-datacenter replication. Node failures don't cause downtime.
Linear scalability. Add nodes, get proportional performance. No sharding complexity.
Write performance. Optimized for high-velocity writes. Time-series data, IoT sensors, event logs.
Key Features
Masterless architecture: No single point of failure, all nodes equal
Tunable consistency: Choose consistency level per query (ONE, QUORUM, ALL)
Wide-column store: Flexible schema with partition keys and clustering columns
CQL: SQL-like query language for familiar syntax
Multi-datacenter replication: Built-in geographic distribution
Pricing
Open Source: Free, Apache 2.0 license (self-hosted)
DataStax Astra: Free tier available, pay-per-usage beyond
AWS Keyspaces: Serverless, pay-per-request pricing
Azure Cosmos DB: Cassandra API available, consumption-based pricing
When to Use It
✅ Multi-datacenter deployments
✅ High write throughput requirements
✅ Time-series or IoT data at scale
✅ Need 99.99%+ availability
✅ Handling billions of rows across distributed nodes
When NOT to Use It
❌ Complex joins and aggregations (limited query flexibility)
❌ Strong consistency requirements (eventual consistency model)
❌ Small datasets (operational overhead not worth it)
❌ Ad-hoc queries (must design for known access patterns)
❌ Limited ops team (requires expertise to run well)
Common Use Cases
Time-series data: Sensor readings, metrics, logs with high write volume
IoT applications: Millions of devices sending data continuously
Product catalogs: E-commerce with global distribution requirements
Messaging platforms: Chat histories, message queues at scale
Fraud detection: Real-time event processing with high availability
Cassandra vs Alternatives
vs MongoDB: Cassandra better for writes and availability, MongoDB better for flexible queries
vs PostgreSQL: Cassandra scales horizontally better, Postgres has richer query capabilities
vs DynamoDB: Cassandra more control and cheaper at scale, DynamoDB fully managed
Unique Strengths
No master node: True peer-to-peer architecture eliminates bottlenecks
Multi-DC writes: Active-active replication across data centers
Proven at scale: Powers Netflix, Apple, Instagram at massive scale
Predictable performance: Linear scalability makes capacity planning easier
Bottom line: Built for scale and availability. If you need multi-datacenter writes, massive throughput, and can't afford downtime, Cassandra delivers. Learn CQL query patterns before committing.