3 repositorios
Parses and compiles SQL statements into reusable execution plans to accelerate recurring data processing tasks.
Distinct from SQL Statement Executions: Distinct from SQL Statement Executions: focuses on the compilation and reuse of execution plans for performance optimization rather than general query execution.
Explore 3 awesome GitHub repositories matching data & databases · Optimized Query Plans. Refine with filters or upvote what's useful.
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
Parses and compiles SQL statements into reusable execution plans to accelerate the performance of recurring data processing tasks.
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
Analyzes query structures to eliminate redundant data shuffling, skip unnecessary aggregation stages, and leverage existing data partitioning.
Ignite es una plataforma de cómputo y rejilla de datos distribuida en memoria. Funciona como una base de datos SQL distribuida y un motor de almacenamiento diseñado para almacenar y procesar grandes conjuntos de datos en RAM para minimizar la latencia y aumentar la velocidad de cálculo. El sistema se distingue por un motor de almacenamiento de varios niveles que gestiona la ubicación de los datos a través de la memoria y el disco para equilibrar el acceso de alta velocidad con una gran capacidad. Cuenta con una rejilla de cómputo distribuida que ejecuta lógica personalizada directamente en los nodos donde residen los datos para reducir el tráfico de red. La plataforma proporciona un amplio conjunto de capacidades, incluyendo gestión de transacciones ACID, consultas SQL estándar y operaciones de clave-valor. Admite la ingesta de datos de alto volumen a través de flujos reactivos y ofrece integración a través de múltiples lenguajes de programación, controladores de base de datos estándar y una API REST. El sistema puede desplegarse como un clúster distribuido utilizando contenedores u orquestarse mediante Kubernetes. El proyecto está escrito en Java y puede instalarse mediante archivos binarios.
Parses standard SQL queries into optimized execution plans tailored for distributed in-memory structures.