Apache Cassandra is an open-source, distributed NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. It's a great choice for managing big data applications where requirements include linear scalability, high performance, and fault tolerance on commodity hardware.
Module 2In this section, we will walk you through the installation process of Apache Cassandra on various platforms like Windows, Linux, and MacOS. We'll also cover essential setup configurations to get your first Cassandra cluster up and running.
Module 3Learn how to model data effectively in Cassandra by understanding keyspaces, tables, and column families. This section will provide best practices for optimizing data storage and retrieval performance.
Module 4Master the basics of CQL, which allows you to query, manipulate, and interact with your Apache Cassandra database efficiently. We'll cover essential CQL commands, functions, and data types to help you get started.
Module 5Optimize your Apache Cassandra performance by implementing best practices for cluster configuration, data modeling, and query optimization. This section will provide actionable tips to ensure your database runs smoothly under high load.
Module 6Explore how to scale Apache Cassandra horizontally across multiple nodes and configure replication for high availability and fault tolerance. This section will cover strategies for handling massive data growth and maintaining strong performance.
Module 7Learn about various backup solutions for Apache Cassandra, including snapshotting and streaming backups. We'll also discuss disaster recovery strategies to ensure your data is protected from unexpected events.
Module 8Understand how to maintain your Cassandra cluster and troubleshoot common issues when they arise by using tools such as "cassandra-stress", the native CLI tool, and other monitoring solutions.
Module 9Understand the real-world applications of Apache Cassandra by exploring various use cases, such as managing social media data, time-series data, IoT device data, and more. We'll provide practical examples to help you visualize the power of this versatile database system.