Awesome GitHub RepositoriesExactly-Once Processing Semantics

Pathway is a high-performance data processing framework designed for building unified batch and streaming pipelines. It functions as an orchestrator for complex data transformations, utilizing a differential dataflow engine to process updates incrementally. By treating static datasets and continuous event streams with identical logic, the platform ensures exactly-once processing semantics and consistent results across diverse data sources. The framework distinguishes itself through its specialized support for real-time artificial intelligence and retrieval-augmented generation. It features in

Apache Flink is a distributed processing engine designed for both high-throughput, low-latency data streams and finite batch workloads. It functions as a stateful stream processor and a SQL stream processing engine, providing a unified runtime to execute relational queries and event-based transformations. The system is distinguished by its ability to manage persistent operator state to ensure exactly-once processing guarantees and consistency during failures. It features specialized capabilities for complex event processing to detect temporal patterns and handles out-of-order events using eve

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, whi

Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations. The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network

NATS Server is a high-performance, lightweight messaging system designed for cloud-native applications, edge computing, and distributed microservices. It functions as a distributed publish-subscribe broker that routes messages using hierarchical, dot-separated subject strings, enabling decoupled communication between services without requiring centralized broker lookups. The system supports core messaging patterns including asynchronous publish-subscribe, request-reply, and load-balanced queue processing. The platform distinguishes itself through a decentralized architecture that eliminates t

Quarkus is a Kubernetes-native Java framework designed for building high-performance, memory-efficient applications. It utilizes ahead-of-time native compilation to transform Java code into standalone, optimized binaries that eliminate the need for a virtual machine, enabling rapid startup and reduced memory consumption. By performing code augmentation during the build phase, it shifts heavy processing tasks away from runtime, ensuring that applications are optimized for cloud-native environments. The framework distinguishes itself through a unified approach to reactive and imperative program

RisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process continuous data streams. It functions as a streaming data lakehouse, combining the capabilities of a streaming SQL database with a platform that integrates streaming ingestion with open table formats. The system is distinguished by its use of the PostgreSQL wire protocol, allowing it to integrate with existing SQL tools and drivers. It employs a decoupled compute and storage architecture, persisting streaming state and materialized views in cloud object storage to enable independen

Storm is a distributed stream processing framework and fault-tolerant compute engine designed for executing real-time continuous computations across a cluster of machines. It functions as a stateful stream processor and cluster topology manager, enabling the deployment and monitoring of distributed data flow configurations. The system ensures exactly-once semantics by utilizing transactional state management to guarantee that every message in a data stream is processed exactly one time. It further operates as a distributed RPC system, allowing for the integration of non-native languages throu

Delta is a lakehouse table format that brings ACID transactions and data warehouse consistency to large scale data lakes on cloud object storage. It serves as an ACID transaction manager, coordinating atomic commits and serializable isolation for concurrent reads and writes across distributed compute engines. The project provides a multi-engine interoperability layer that uses format translation to allow diverse SQL engines and processing frameworks to read and write the same tables. It functions as a data versioning system, utilizing a transaction log to enable time travel, historical snapsh

BullMQ is a Redis-backed message queue library and background processor designed for distributed task queueing. It functions as a distributed queue manager and task scheduler, utilizing Redis to manage asynchronous job processing and persistence. The system distinguishes itself through its role as a job workflow orchestrator, enabling the definition of complex parent-child job dependencies and hierarchies for multi-step workflows. It provides sandboxed process execution to isolate heavy workloads and prevent event loop blocking, alongside distributed rate limiting to protect downstream servic

Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis

Hatchet is an open-source durable workflow engine and task orchestration platform. It provides a framework for building and executing fault-tolerant, multi-step pipelines as directed acyclic graphs (DAGs), with automatic retries, scheduling, and real-time observability. The system is built around durable task checkpointing, which persists execution state after each step so work can resume from the last checkpoint after a worker crash or restart, and it supports event-driven task resumption that pauses a task until a matching external event arrives. The platform distinguishes itself through it

This project is a streaming data integration framework that captures real-time database changes and synchronizes them with downstream systems. It operates as a distributed streaming ETL and database synchronizer, reading database logs and snapshots to propagate row-level modifications to target sinks. The system supports declarative data integration, allowing users to define source-to-sink data flows using SQL or YAML configurations. It distinguishes itself by automating schema evolution to maintain synchronization when source structures change and ensuring exactly-once delivery and processin

Ce projet est une référence technique et une collection de notes d'analyse interne axées sur le runtime et le compilateur du langage Go. Il fournit une analyse détaillée des rouages internes du langage, couvrant la gestion de la mémoire, le ramasse-miettes (garbage collection) et le modèle d'exécution du planificateur. Le matériel se distingue en fournissant des plongées approfondies dans les détails système de bas niveau, incluant une référence pour les instructions d'assemblage Go, l'utilisation des registres et l'interfaçage des appels système. Il analyse spécifiquement l'implémentation interne des primitives de concurrence, telles que le mécanisme de planification des goroutines, les opérations sur les canaux et les implémentations de verrous mutex. La couverture s'étend à la théorie de la construction des compilateurs, incluant l'analyse lexicale et syntaxique, ainsi que la mécanique du système de types et la gestion des interfaces. Il détaille également diverses techniques d'optimisation des performances, des utilitaires de diagnostic du runtime pour le traçage de la pile et des primitives d'E/S réseau.

AWS Powertools for Python is a utility framework designed for building production-ready Python functions on AWS Lambda. It provides a comprehensive suite of tools for observability, event parsing, routing, and idempotency management to streamline the development of serverless applications. The project distinguishes itself through specialized capabilities for event-driven architectures and AI agent orchestration. It enables the implementation of AI agents by exposing functions as tools via OpenAPI schemas and managing conversation states. Additionally, it features an idempotency library that p

This project is a reference library of architectural blueprints, study materials, and design patterns for building scalable, high-availability distributed systems. It serves as a technical guide for scalability engineering, providing structural solutions for common engineering challenges. The repository focuses on distributed systems design, covering essential patterns for data replication, consensus algorithms, and transaction management. It distinguishes itself by offering detailed blueprints for specialized domains, including real-time data streaming, large-scale data storage, and high-ava