Apache Cassandra: An open-source, highly scalable, distributed NoSQL database system designed for handling large volumes of data with high availability.
Advantages
- Scalability: Horizontally scalable to handle massive data loads.
- High Availability: Data replication for fault tolerance.
- Linear Performance: Performance improves with cluster size.
- No Single Point of Failure: Resilient architecture.
- Flexible Schema: Supports dynamic and complex data models.
Disadvantages
- Complexity: Requires expertise in distributed databases.
- Consistency Trade-offs: Tuning consistency levels can be complex.
- Query Language: CQL may not be as powerful as SQL for some use cases.
- Data Modeling Challenges: Requires careful planning for optimal performance.
- Operational Complexity: Maintenance and monitoring can be demanding.
Components
- Nodes: Individual instances in the Cassandra cluster.
- Keyspaces: Equivalent to databases in Cassandra.
- Column Families (Tables): Stores data in a structured format.
- Replication: Copies data to multiple nodes for fault tolerance.
- Query Language (CQL): Cassandra Query Language for data manipulation.
Development tools
- Cassandra Query Language (CQL): For interacting with Cassandra.
- DataStax DevCenter: A graphical interface for querying and managing data.
- Apache Cassandra Drivers: Language-specific drivers for application integration.
- Cassandra Monitoring Tools: Various monitoring tools for cluster health and performance.
- Cassandra Stress Tool: For simulating workloads and testing clusters.