Awesome GitHub RepositoriesQuery Planning

Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e

Prefect is a workflow orchestration platform designed to define, schedule, and monitor complex data pipelines as Python code. It functions as a container-native engine that wraps individual tasks in isolated environments, ensuring consistent dependencies and resource allocation across diverse infrastructure. By utilizing a state-machine-based orchestration model, the system tracks execution progress through discrete transitions and persistent event logs to maintain reliable and observable task processing. The platform distinguishes itself through a decoupled worker-API architecture, which sep

ip2region is an offline IP geolocation library and framework designed to resolve IPv4 and IPv6 addresses to city-level regional information using local binary data files. It functions as a binary IP database compiler and a cross-language search client, allowing for regional lookups without relying on external APIs. The project distinguishes itself through a specialized binary format that supports high-performance query optimization. It employs adjacent-segment IP merging and deduplicated region storage to minimize the database footprint, while utilizing memory-mapped file caching and vector-i

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

Apache Druid is a real-time analytics database and distributed columnar time-series store designed for sub-second analytical queries. It functions as a data platform featuring a distributed SQL query engine and a real-time data ingestion system for moving historical and streaming data from external sources. The system is distinguished by its ability to provide low-latency analytics under high concurrency to power operational dashboards. It implements a Kerberos-secured environment for user authentication and employs a shared-nothing cluster architecture to enable horizontal scaling. The plat

Dask est un framework de calcul parallèle et un planificateur de tâches distribué conçu pour mettre à l'échelle les flux de travail de science des données Python, des machines uniques aux grands clusters. Il fonctionne comme un gestionnaire de ressources de cluster qui orchestre la logique computationnelle en représentant les tâches et leurs dépendances sous forme de graphes acycliques dirigés. Cette architecture permet au système d'automatiser la distribution des charges de travail sur le matériel disponible tout en gérant des exigences d'exécution complexes. Le projet se distingue par un moteur d'évaluation paresseuse qui diffère les opérations sur les données jusqu'à ce qu'elles soient explicitement demandées, permettant une optimisation globale du graphe et une allocation efficace des ressources. Il intègre le déversement de données conscient de la mémoire pour éviter les plantages du système lors du traitement de jeux de données dépassant la mémoire disponible, et il utilise la fusion de graphes de tâches pour combiner des séquences d'opérations en étapes d'exécution uniques, minimisant la surcharge de planification et la communication entre nœuds. La plateforme fournit une surface de capacités complète pour l'analyse de données à grande échelle, incluant le support pour l'apprentissage automatique distribué, l'intégration du calcul haute performance et le traitement de données parallèle. Elle offre des outils étendus pour la gestion du cycle de vie des clusters, le profilage des performances et la surveillance en temps réel de l'exécution des tâches. Les utilisateurs peuvent déployer ces environnements sur diverses infrastructures, incluant le matériel local, les fournisseurs cloud, les systèmes conteneurisés et les clusters de calcul haute performance.

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PostGraphile is an automated tool that converts a PostgreSQL database schema into a fully functional GraphQL API. It serves as a GraphQL execution engine and schema orchestrator, utilizing database schema introspection to retrieve strongly typed metadata directly from PostgreSQL. The project features a modular system for composing and standardizing GraphQL schemas through plugins, which manage naming conventions and connections. It includes a PostgreSQL query builder that constructs dynamic, SQL-injection-proof queries using tagged template literals. The system employs a declarative query pl

The AWS Cloud Development Kit is an infrastructure-as-code framework that enables developers to define and provision cloud resources using familiar programming languages. By utilizing construct-based synthesis, it translates high-level, object-oriented code into declarative templates, allowing for the automated management of complex cloud environments through a centralized, code-driven control plane. The framework distinguishes itself through its ability to model infrastructure as a dependency-aware resource graph, ensuring that components are provisioned and updated in the correct order. It

This project is a curated collection of academic papers, books, and technical resources designed for studying the architecture and implementation of database management systems. It serves as a comprehensive educational guide for engineers and researchers looking to understand the fundamental principles behind modern data storage and retrieval. The repository distinguishes itself by providing structured learning paths across critical database domains, including the design of persistent storage engines, the mechanics of query optimization, and the complexities of distributed transaction managem

This project is a GraphQL implementation for Go, providing a complete suite for building GraphQL servers. It includes a schema engine for defining types, a query parser to convert strings into abstract syntax trees, and an execution engine that resolves fields against a defined schema to return structured data. The library distinguishes itself through reflection-based type mapping, allowing object definitions and arguments to be derived directly from native Go structs. It also supports the execution of real-time data streaming via GraphQL subscriptions and provides an extensible execution pip

sqlglot is a SQL parser and transpiler that represents queries as abstract syntax trees to enable structural analysis, modification, and semantic transformation. It functions as a dialect translator and query optimizer, converting SQL code between different database engines and simplifying syntax trees through rule-based normalization. The project provides a framework for defining custom SQL dialects by overriding tokenizers, parsers, and generators. It includes a lineage analyzer to track data flow from source tables through complex queries to identify the origin of specific columns. Additi

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

Apache DataFusion is an extensible, columnar SQL query engine that runs embedded within a host application without requiring a separate server process. It processes data in columnar batches using Apache Arrow for memory-efficient analytics, and can scale analytic workloads across multiple nodes for parallel execution. The engine supports both SQL and DataFrame queries through a modular, streaming architecture that allows custom operators, data sources, functions, and optimizer rules. The engine distinguishes itself through its modular extension framework, which enables building custom query e

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

ToyDB is a distributed SQL database that provides a system for storing and querying data across multiple nodes. It focuses on maintaining strong consistency and fault tolerance through the implementation of a distributed consensus algorithm. The project distinguishes itself by supporting historical data versioning, enabling time-travel queries to retrieve the state of the database from a specific point in the past. It utilizes multi-version concurrency control to manage ACID transactions and ensure data integrity during concurrent operations. The system covers relational data modeling with t

SpiceDB is a distributed permission store and relationship-based access control system. It provides a scalable database for storing and querying fine-grained authorization relationships, implementing a consistency model inspired by Google Zanzibar to manage access rights across large-scale applications. The system uses a dedicated schema language to define the rules and logic governing how relationships translate into permissions independently of application code. It functions as a pluggable authorization engine that persists relationship tuples in external relational databases such as Postgr

Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma

Boxplayer is a cloud media player and storage manager that enables high-definition video streaming and file administration across multiple cloud storage providers through a unified interface. It functions as a cloud media player with subtitle and audio support, a metadata organizer for structuring media libraries, and a high-speed download manager using a multi-threaded engine. The project implements a Model Context Protocol server, which exposes cloud storage and media management functions as programmable tools and context for AI agents. This allows for AI-driven storage automation and the a

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