Awesome GitHub RepositoriesCustom Aggregation Function Writing

AlaSQL is a JavaScript SQL database engine that allows for the filtering, grouping, and joining of in-memory object arrays and JSON data. It functions as an in-memory SQL database and client-side data processor, enabling the execution of SQL statements against JavaScript arrays and external data sources in both browser and server environments. The project serves as a universal data query tool capable of performing relational joins across diverse sources, such as merging Google Spreadsheets, SQLite files, and remote APIs into a single result set. It also acts as an IndexedDB SQL wrapper, allow

Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

Apache Hive is a SQL-on-Hadoop data warehouse that enables querying and managing petabytes of data stored in distributed storage such as HDFS and cloud storage services. It provides a familiar SQL interface for batch analytics and reporting, supported by a core set of components including the HiveServer2 Thrift service for remote query execution, the Hive Metastore Service for central metadata management, the Hive ACID Transaction Engine for concurrent read-write operations, and the Hive LLAP Interactive Engine for low-latency analytical processing. The WebHCat REST API offers an HTTP interfac

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

H2 is a JDBC-compliant relational database management system written in Java. It functions as an embeddable SQL database that can run directly within an application process to remove network latency, or as an in-memory database for high-performance volatile storage. It also includes a web-based console for executing SQL commands and administering schemas. The system is characterized by its flexible deployment modes, including a standalone server mode for remote TCP/IP access and a mixed mode for simultaneous local and remote connectivity. It features a dialect emulation layer and compatibilit

Velox est un moteur d'exécution de requêtes C++ haute performance et une bibliothèque de traitement de données colonnaires. Il sert de framework composable pour implémenter des moteurs de requêtes analytiques, fournissant un évaluateur d'expressions vectorisées et une boîte à outils pour les systèmes de gestion de données. Le projet se distingue par son utilisation de l'exécution colonnaire vectorisée et de l'allocation mémoire basée sur des arènes pour traiter des jeux de données à grande échelle. Il propose des optimisations spécialisées telles que la mise en cache des tables de jointure broadcast, le push-down de filtres dynamiques et l'encodage par dictionnaire pour réduire la surcharge mémoire et accélérer les lectures analytiques. Le moteur couvre un large éventail de capacités analytiques, incluant l'implémentation de jointures hash, merge et semi, ainsi que l'agrégation parallèle multi-étapes et le calcul de fonctions de fenêtre. Il fournit des primitives pour le stockage colonnaire en mémoire, le décodage de données Parquet et l'intégration avec le stockage cloud. L'extensibilité est assurée par un système d'enregistrement de fonctions pour des fonctions scalaires et d'agrégation personnalisées, avec des bindings de haut niveau disponibles pour connecter la logique C++ à Python.