This project serves as a comprehensive technical reference for the architecture and design of data-intensive applications. It provides a structured analysis of the fundamental principles required to build reliable, scalable, and maintainable software systems, covering the core trade-offs inherent in modern data infrastructure.
The repository explores the mechanics of distributed data management, including strategies for replication, partitioning, and achieving consensus across multiple nodes. It details the design of storage engines, indexing techniques, and transaction management models, while also examining the architectural patterns for both batch and stream processing pipelines.
Beyond foundational theory, the project covers the implementation of event-driven systems, including event sourcing, log-structured storage, and message brokering. It addresses the complexities of maintaining system consistency, enforcing transactional integrity, and managing derived data views in environments prone to network failures and concurrency challenges.
The documentation is available in multiple formats, including an exportable digital book version, to support study and reference across various devices.
