Awesome GitHub RepositoriesFederated Databases

Ce projet est une ressource éducative et un guide d'étude complet axé sur l'architecture des systèmes distribués et la conception d'infrastructures backend. Il fournit un programme structuré pour maîtriser les principes de scalabilité, de fiabilité et de performance requis pour concevoir des systèmes logiciels complexes. Le dépôt se distingue en offrant une approche méthodique de la préparation aux entretiens techniques, intégrant des modèles de conception, des compromis architecturaux et des outils de répétition espacée pour aider les utilisateurs à retenir des concepts complexes. Il met l'accent sur l'analyse axée sur les contraintes, enseignant aux utilisateurs comment évaluer des exigences concurrentes comme la latence, la cohérence et la disponibilité lors de l'élaboration de conceptions architecturales. Le contenu couvre un large spectre de capacités de conception de systèmes, notamment des stratégies pour la mise à l'échelle des bases de données, la gestion du trafic et l'optimisation de l'infrastructure. Il détaille des techniques pour la mise à l'échelle horizontale, la mise en cache multicouche, la communication asynchrone et la découverte de services, tout en fournissant des cadres pour effectuer des estimations de ressources et la planification de la capacité. La documentation est organisée comme un guide d'étude, offrant un chemin systématique à travers les fondamentaux de l'ingénierie backend et de la conception de systèmes à grande échelle.

This project is a comprehensive educational resource focused on the principles, patterns, and trade-offs required to design scalable, reliable, and high-performance distributed systems. It provides a structured curriculum that covers the fundamental architectural strategies necessary for building modern software infrastructure, ranging from high-level system decomposition to low-level networking and data management. The repository distinguishes itself by offering deep dives into complex architectural patterns, such as microservices-based decomposition, event-driven communication, and command-

Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing

gqlgen is a schema-first Go library designed to build type-safe GraphQL servers. It functions as a code generation engine that transforms declarative GraphQL schema definitions into strongly-typed Go source code, ensuring strict alignment between the API contract and the underlying implementation. The framework distinguishes itself through its deep integration with the Go type system and its highly extensible build pipeline. By using schema-first development, it automates the creation of server boilerplate and resolver stubs, allowing developers to map schema fields directly to Go structs and

LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters