pingcap/awesome-database-learning

Features

• Database Internals - Serves as a comprehensive educational guide for studying the fundamental architecture and internal mechanics of database management systems.
• Database Architectures - Offers a structured learning path for understanding the fundamental design principles and architecture of modern database systems.
• Database Learning Guides - Serves as a curated educational guide and learning path for mastering database system architecture and implementation.
• Awesome List - A community-curated directory that catalogs and links out to other open-source projects, rather than a standalone tool you run yourself.
• Distributed Consensus Protocols - Covers consensus algorithms and voting mechanisms essential for maintaining state consistency across distributed database nodes.
• Distributed Transaction Processing - Provides comprehensive educational resources on consensus protocols and consistency mechanisms for distributed transaction processing.
• Multi-Version Concurrency Control - Explains the architecture of multi-version concurrency control for enabling simultaneous read and write access without blocking.
• Cost-Based Optimizers - Offers technical resources on cost-based query optimization strategies using statistical data to determine efficient execution paths.
• Storage Engines - Offers detailed technical documentation and study materials on the internal architecture and design of database storage engines.
• B-Tree - Provides educational resources on B-Tree structures for organizing sorted data pages to optimize disk access and search operations.
• Database Query Optimization - Provides a structured educational progression for understanding query planning, cost modeling, and execution optimization.
• Database Systems - Educational resources on database internals.
• Databases & Data Processing - Resources for learning about database internals.
• Concurrency Control - Provides resources on isolation levels and concurrency control to maintain data integrity during simultaneous access.
• Distributed Databases - Provides in-depth study materials on distributed database architectures, replication strategies, and consistency models.
• Performance and Optimization Tools - Provides research on query planning and execution strategies to optimize database performance.
• Database Query Optimizations - Explores query optimization techniques including cost modeling and join ordering to improve data retrieval efficiency.
• Indexing and Search - Covers indexing strategies like trees and logs to accelerate search operations and minimize disk activity.
• Log-Structured Storage - Provides documentation on log-structured storage engines that use sequential appends to optimize write performance and recovery.
• Query Planning - Covers query planning and execution strategies to minimize processing time for complex data requests.
• Vectorized Execution Engines - Covers vectorized query execution models that process data in batches to maximize CPU cache efficiency.
• Just-in-Time Compilers - Explores just-in-time compilation techniques for translating database queries into machine code to reduce execution overhead.
• Execution Performance Analyzers - Analyzes high-performance execution models like operator fusion and vectorization for efficient query processing.
• Performance Benchmarking - Provides methodologies for benchmarking database performance, including throughput and latency analysis under various workloads.

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