Apache Cassandra

Apache Cassandra is an open-source, distributed NoSQL database management system designed for high availability, scalability, and fault tolerance. It was originally developed by Facebook and later open-sourced as part of the Apache Software Foundation.

Syllabus:

• Module 1: Introduction to Apache Cassandra
• Overview of NoSQL databases and Cassandra.
• History and evolution of Cassandra.
• Cassandra’s features and use cases.
• Distributed database concepts.
• Module 2: Cassandra Data Model
• Understanding the Cassandra data model (tables, rows, columns).
• Primary keys and clustering columns.
• Data types in Cassandra.
• Composite keys and collections (sets, lists, maps).
• Module 3: Data Modeling in Cassandra
• Best practices for data modeling.
• Denormalization and designing for queries.
• Understanding the CAP theorem in the context of Cassandra.
• Creating and managing tables in Cassandra.
• Module 4: Querying Data in Cassandra
• CQL (Cassandra Query Language) basics.
• SELECT statements and filtering data.
• UPDATE, DELETE, and INSERT operations.
• Batch operations and lightweight transactions.
• Module 5: Data Distribution and Replication
• Cassandra’s distributed architecture.
• Partitioning and data distribution.
• Replica placement and consistency levels.
• Handling data distribution and replication for high availability.
• Module 6: Tuning and Optimization
• Monitoring and metrics in Cassandra.
• Tuning Cassandra for performance.
• Compaction and compression strategies.
• Handling large-scale data.
• Module 7: Security in Cassandra
• Authentication and authorization.
• Encryption and SSL/TLS.
• Data encryption at rest.
• Securing Cassandra clusters.
• Module 8: Backup and Recovery
• Backup strategies and options.
• Point-in-time recovery.
• Backup and restore procedures.
• Data durability and fault tolerance.
• Module 9: Apache Cassandra Operations
• Deploying Cassandra clusters.
• Managing nodes and adding/removing nodes.
• Maintenance and upgrades.
• Troubleshooting common issues.
• Module 10: Integrations and Ecosystem
• Using drivers and client libraries (Java, Python, etc.).
• Integrating Cassandra with other technologies (Spark, Elasticsearch, etc.).
• Exploring the Cassandra ecosystem and tools.
• Module 11: Use Cases and Real-World Examples
• Case studies and examples of Cassandra in production.
• Architectural patterns and best practices for specific use cases.
• Building scalable and fault-tolerant applications.
• Module 12: Advanced Topics (Optional)
• Time-series data modeling.
• Multi-datacenter and cross-region replication.
• Consistency and tunable consistency.
• Advanced troubleshooting and performance optimization.