Awesome GitHub RepositoriesSQL-Based Machine Learning

Minds Platform is an automation system and application platform designed for building and deploying custom AI tools and workflows. It functions as a machine learning integration layer and self-hosted orchestrator that connects predictive models and large language models to external data sources. The platform enables the execution of multi-step tasks that read and write data to automate reports and operational activities. It supports deployment across cloud, on-premises, and virtual private cloud environments to maintain control over models and data. Capabilities include event-driven workflow

MindsDB is an AI-native database engine that treats machine learning models and autonomous agents as virtual tables. By mapping external data sources, predictive models, and third-party services directly into the database schema, it enables users to perform inference, data retrieval, and complex orchestration using standard SQL syntax. The platform distinguishes itself through an autonomous agent orchestrator that executes iterative reasoning loops, allowing agents to plan data access and synthesize natural language responses from connected knowledge bases. It functions as a federated data ga

This is a reference implementation library providing a collection of code samples, Transact-SQL scripts, and schemas for SQL Server, Azure SQL, and Azure Synapse. It focuses on providing standardized implementation patterns and reference code for building relational databases and cloud data warehouses. The library distinguishes itself by offering specialized guides and examples for deploying database instances within containerized environments and Azure cloud services. It includes specific reference databases and language extensions for integrating machine learning services and advanced analy

PostgresML is a machine learning database extension for PostgreSQL that integrates model training and inference directly into the database. It functions as an in-database AI platform and vector database, enabling the execution of large language models and natural language processing tasks on stored records without exporting data to external services. The system distinguishes itself by utilizing GPU acceleration to minimize latency during model predictions and employing a hybrid storage engine that maintains relational data alongside high-dimensional vectors. It allows for the building and fin

pgai ist ein PostgreSQL-KI-Toolkit und -Framework, das darauf ausgelegt ist, Large Language Models und Vektor-Embeddings direkt in eine Datenbank zu integrieren. Es dient als Brücke für die Ausführung von Anfragen an Machine-Learning-Modelle und die Durchführung von Text-zu-SQL-Übersetzungen innerhalb von Standard-Datenbankabfragen. Das Projekt bietet eine automatisierte Pipeline für Vektor-Embeddings, die das Laden, Parsen und Chunking von Text aus Tabellen und unstrukturierten Dokumenten übernimmt. Dieses System nutzt einen Hintergrund-Worker, um Embeddings automatisch zu synchronisieren, wenn sich Quelldaten ändern, und enthält spezialisierte Tools für den Aufbau von RAG-Anwendungen (Retrieval-Augmented Generation) und semantischen Suchmaschinen. Das Toolkit deckt breite Funktionsbereiche ab, darunter die Verarbeitung unstrukturierter Daten mittels OCR, die Erstellung semantischer Kataloge zur Abbildung von Datenbankschemata auf natürliche Sprache sowie die Implementierung von Hochleistungs-Ähnlichkeitssuchen durch Vektorindizierung und Result-Reranking. Zudem ermöglicht es Datenanreicherung, Klassifizierung und Content-Moderation durch den Aufruf externer Modelle via SQL.

sqlflow is a SQL machine learning engine and orchestrator designed for training, deploying, and explaining machine learning models using extended SQL query syntax. It enables in-database machine learning by connecting database engines to external machine learning toolkits, allowing users to define training datasets and hyperparameters directly through queries. The system functions as a prediction interface and explainability tool. It allows for generating classifications and predictions on database records by calling model functions within standard SQL statements and provides a workflow to in