4 dépôts
Executes streaming pipelines as a directed acyclic graph of parallel subtasks, routing data across workers via forward or shuffle edges.
Distinct from Directed Acyclic Graph Execution Engines: Candidates are either ML-specific (Distributed Execution) or symbolic-execution-specific (Directed Acyclic Graph Execution Engines); no existing tag covers distributed execution of stream processing DAGs.
Explore 4 awesome GitHub repositories matching data & databases · Distributed Stream Execution. Refine with filters or upvote what's useful.
Apache Storm is a distributed stream processing framework and real-time data processing engine. It functions as a fault-tolerant distributed computing system designed to analyze data in motion across a cluster of machines for continuous stream computation. The system enables the creation of fault-tolerant data pipelines and scalable event processing by distributing workloads across a network of computing nodes. This architecture ensures low latency and high throughput for live data while allowing the system to recover automatically from individual node failures. The framework provides capabi
Executes streaming pipelines as a directed acyclic graph distributed across a cluster of worker nodes.
Octosql est un moteur de requête SQL fédéré, un transformateur de données et un processeur SQL de flux. Il permet aux utilisateurs d'exécuter des instructions SQL uniques sur plusieurs sources de données disparates, y compris différents types de bases de données et formats de fichiers, afin de fusionner et transformer les résultats en un ensemble unifié. Le système se distingue en traitant les fichiers CSV, JSONLines et Parquet comme des tables virtuelles et en utilisant une architecture basée sur des plugins pour étendre la connectivité aux moteurs de stockage externes. Il fonctionne comme un processeur de flux pour les flux de données infinis, utilisant des filigranes (watermarks), des rétractions et des fenêtres glissantes pour maintenir la cohérence des événements hors séquence. De plus, il sert de générateur de données SQL capable de produire des jeux de données synthétiques et des flux d'enregistrements via des fonctions table. Le moteur inclut des capacités de jointure de données inter-sources et d'analyse multi-sources, optimisées par le push-down de prédicats côté source pour réduire le transfert de données. Il gère des données complexes via un système de typage statique avec des types union et offre une observabilité grâce à la visualisation des plans d'exécution de requêtes.
Executes queries on endless data streams using watermarks and retractions to handle out-of-order events.
Arroyo is a high-performance stream processing platform built in Rust. It executes continuous SQL queries on streaming data with event-time semantics, enabling accurate windowed aggregations, joins, and stateful computations on unbounded event streams. The platform uses native Rust execution for high throughput and low latency, with periodic checkpointing for exactly-once fault tolerance and horizontal scaling across distributed workers. The system integrates deeply with Kafka for reading and writing topics with exactly-once delivery and supports change data capture (CDC) from MySQL and Postg
Executes streaming pipelines as a distributed DAG of parallel subtasks for high throughput and fault tolerance.
vim-dadbod is a database interface for the Vim editor that allows for the execution of SQL and NoSQL queries. It functions as a connection manager and query runner, enabling users to interact with databases using connection URLs. The project acts as a bridge to native command-line interfaces, providing a wrapper to launch interactive database consoles. This integration allows users to run commands from the editor and view the results within a preview window. The system manages database connections through URL-based configurations and environment variables. It handles the execution of queries
Streams editor buffer contents to external database binaries for query execution.