Awesome GitHub RepositoriesQuery Execution Engines

ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad

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

RethinkDB is a distributed, document-oriented database designed to store and manage JSON-formatted data across scalable clusters. It utilizes a custom log-structured storage engine with B-Tree indexing to ensure high-performance disk I/O and data persistence. The system maintains high availability through automatic sharding and replication, employing a primary-replica voting consensus mechanism to handle node failures and ensure consistent cluster operations. A defining characteristic of the platform is its reactive changefeed engine, which allows applications to subscribe to live data update

Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

DB-GPT is an agentic data analysis platform and business intelligence AI that functions as a large language model data assistant. It provides a text-to-SQL interface and a sandboxed code execution environment to translate natural language into executable database queries and Python scripts. The platform utilizes iterative agentic reasoning to plan and execute multi-step data analysis workflows through tool calls. It features a modular skill-based extension system that allows domain knowledge and analysis workflows to be packaged into reusable functional components. The system integrates data

Gel is an object-relational database system that models data as a graph of interconnected objects. By utilizing a strongly typed schema, it enables complex relational queries and polymorphic data structures without the need for traditional join tables. The system integrates native vector storage and similarity search operators, allowing it to function as both a relational and a vector database for semantic data retrieval. The platform distinguishes itself through a comprehensive suite of developer-centric automation tools. It features a declarative migration system that tracks and versions sc

OpenBrowser is an AI web agent toolkit and automation framework designed to translate natural language instructions into executable browser workflows. It functions as a headless browser controller and orchestrator, enabling the creation of autonomous agents that navigate websites, interact with elements, and extract data using plain English commands. The system features a sandboxed execution environment that utilizes domain whitelists and memory limits to ensure secure web interaction. It distinguishes itself through a command-line interface for triggering autonomous tasks with configurable m

LiteDB is a serverless, embedded NoSQL document database for .NET applications. It persists data into a single portable file, functioning as a BSON data store that resides within the application process rather than running as a separate server. The system is ACID compliant, utilizing write-ahead logging to ensure atomic, consistent, isolated, and durable transactions. It includes built-in encryption to provide secure local data storage and protect files on disk from unauthorized access. The project covers object-document mapping to convert classes into document formats, indexed search capabi

AI Town is a TypeScript-based simulation engine used to create virtual environments where autonomous characters interact and socialize. It functions as a framework for orchestrating multiple AI agents within a persistent digital world, utilizing language models and a game engine to drive character behavior and social interactions. The project differentiates itself through a dedicated agent sandbox and a vector database agent store, which allow for the management of agent memories and world state. It integrates generative AI for background music and provides tools for simulation world design,

Oatpp is a high-performance C++ web framework and API development kit used for building REST APIs and web services. It functions as an asynchronous HTTP server that utilizes coroutines to handle thousands of simultaneous connections without blocking threads. The toolkit includes a native C++ object-relational mapping layer for executing SQL queries and transforming database results into data objects. It also provides a WebSocket communication library for establishing full-duplex channels to support real-time data streaming and live media. The framework covers a broad range of capabilities, i

DevOps-Bash-tools is a collection of shell scripts and aliases designed to automate cloud infrastructure, container orchestration, and CI/CD pipelines. It provides a comprehensive toolset for managing operational workflows through the command line. The project specializes in automating tasks across multiple platforms, including managing namespaces and secrets in Kubernetes, auditing resources in AWS and GCP, and triggering builds or managing environment variables in GitHub Actions, GitLab CI, and CircleCI. It also includes a toolkit for interacting with container registries to query manifests

Forgecode is an AI agent orchestrator, shell integration tool, and terminal-based pair programmer. It enables the deployment of specialized AI roles for research, planning, and implementation, while providing a semantic code search tool to index project files for meaning-based retrieval. The system integrates as a Model Context Protocol client to extend AI capabilities via external servers and supports multi-provider model orchestration to switch between different large language model APIs. It transforms natural language into functional shell commands and allows for the execution of AI prompt

This project is a Rust-based AI agent framework and tool orchestrator that provides a command-line interface for interacting with large language models. It functions as an AI tool orchestrator that routes client requests to language servers and manages the planning and handoffs between specialized agents to solve complex tasks. The system distinguishes itself as a language porting validator, using deterministic mocks and specifications to verify feature parity between different language implementations of a codebase. It further extends agent capabilities by acting as a Model Context Protocol

Ibis is a portable Python dataframe library and multi-backend query engine that provides a unified interface for executing data transformations across diverse compute engines. It functions as a Python SQL expression compiler and dialect transpiler, allowing users to define data logic once and execute it across cloud warehouses, embedded databases, and distributed clusters without rewriting code. The project distinguishes itself through a database backend abstraction that decouples transformation logic from the underlying execution engine. It enables polyglot data workflows by mixing raw SQL s

Kimi is a terminal-based AI agent that autonomously plans and executes software development tasks by reading, editing, and running code. It operates as an intelligent command-line agent that breaks down high-level goals into sequences of shell commands and code edits, carrying them out without manual step-by-step guidance. The agent can run in an interactive loop, switch to a shell mode for direct terminal command execution, and operate in non-interactive or one-shot modes suitable for scripting. The project distinguishes itself through multiple integration and execution modes. It can run as

TaskWeaver is an LLM agent framework that interprets natural language requests and executes them as Python code, SQL queries, or shell commands. It functions as a conversational code interpreter that maintains stateful data structures across turns, generating executable code from user prompts within a session-based environment. The system is designed as a self-hosted AI agent platform that can be deployed in Docker, managing sessions and providing a web UI for data analytics and automation tasks. The framework distinguishes itself through a role-based multi-agent architecture that divides the

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

Lux est un outil d'analyse exploratoire de données automatisé conçu pour générer des représentations visuelles intelligentes de dataframes pandas. Il identifie les modèles et les tendances en recommandant les types de graphiques et les mappings d'axes optimaux basés sur les attributs statistiques d'un jeu de données. L'outil fonctionne comme une couche de profilage de données interactive qui permet aux utilisateurs de parcourir et d'interroger des collections de graphiques en utilisant des filtres et des wildcards. Il sert également de générateur de code de visualisation, traduisant les graphiques produits automatiquement en code programmatique ou en HTML pour un affinement manuel dans des bibliothèques externes. Le système couvre un large éventail de capacités d'analyse exploratoire, notamment l'encodage automatique de graphiques, la découverte guidée via des recommandations d'étapes, et la capacité d'exporter des configurations visuelles sous forme de spécifications déclaratives. Ce projet s'intègre directement dans pandas pour remplacer l'affichage par défaut des dataframes par des composants de visualisation interactifs.

Ce projet est un outil d'analyse statique alimenté par l'IA et un scanner de vulnérabilités automatisé conçu pour détecter les failles de sécurité telles que les injections et les contournements d'authentification. Il utilise des grands modèles de langage pour effectuer un raisonnement sémantique à travers plusieurs langages de programmation, identifiant les vulnérabilités au sein des changements de code. L'outil fonctionne comme une GitHub Action qui s'intègre dans les pipelines d'intégration continue pour analyser les diffs de pull request. Il se concentre sur les lignes de code modifiées pour cibler les nouveaux risques et rapporte les résultats en publiant des commentaires automatisés directement sur la pull request. L'analyse est dirigée par des politiques de sécurité personnalisables et l'injection de règles externes, permettant des instructions spécifiques au projet. Ces règles et filtres personnalisés sont utilisés pour réduire le bruit et écarter les résultats à faible impact afin de prioriser les risques de sécurité à haute confiance.

Ce projet est une collection complète de matériel pédagogique de programmation Python, y compris des tutoriels, des exercices et des exemples de code organisés. Il sert de programme d'apprentissage et de boîte à outils d'ingénierie logicielle, utilisant des Jupyter Notebooks pour combiner du code exécutable avec un texte éducatif descriptif. Le dépôt fournit des guides d'implémentation pratiques pour construire des applications de grand modèle de langage, telles que des systèmes de génération augmentée par récupération, des agents IA avec état et des flux de travail d'apprentissage automatique. Il se distingue en offrant une approche structurée des flux de travail de codage agentique, couvrant la distillation de la fenêtre de contexte, le routage de modèle agnostique au fournisseur et les sorties structurées imposées par schéma. Le matériel couvre un large éventail de capacités d'ingénierie logicielle, notamment la programmation asynchrone avec des files d'attente de tâches distribuées, le développement d'applications web avec des API REST et les flux de travail d'analyse de données. Il inclut également des ressources pour maîtriser la conception orientée objet, implémenter des pipelines CI/CD et appliquer des normes professionnelles de linting et de formatage.