13 Repos
Drivers and utilities for querying relational databases.
Distinguishing note: Focuses on database connectivity and query execution.
Explore 13 awesome GitHub repositories matching data & databases · SQL Database Connectors. Refine with filters or upvote what's useful.
Pandas is a high-performance data analysis library that provides a comprehensive framework for manipulating, cleaning, and transforming structured datasets. It centers on labeled one-dimensional and two-dimensional data structures, allowing users to construct, filter, and reshape tabular information while performing complex arithmetic and logical operations. The library distinguishes itself through a sophisticated indexing engine that enables automatic data alignment during calculations and relational merges. By utilizing a block-based memory layout, it optimizes cache locality for vectorized
Retrieves and writes data to relational databases using flexible query execution.
Appsmith is a low-code platform designed for building internal business tools, such as operational dashboards and administrative panels. It enables developers to construct dynamic user interfaces by dragging and dropping modular widgets onto a canvas and binding them directly to backend data sources. The platform utilizes a reactive framework that automatically updates interface elements and triggers functions whenever underlying data or widget properties change, eliminating the need for manual event handling. The platform distinguishes itself through a server-side proxy architecture that exe
Retrieves, filters, inserts, and updates records in SQL databases using standard query clauses to manage relational data.
This project is a privacy-focused, self-hosted metasearch engine that aggregates results from a wide array of web, academic, and media sources into a single, unified interface. By acting as a proxy between the user and external search providers, it strips identifying headers and tracking parameters from requests, ensuring that search activity remains anonymous and protected from third-party profiling. The platform distinguishes itself through a modular, plugin-based architecture that allows for extensive customization of search behavior, result filtering, and interface branding. It supports a
Connects relational databases to retrieve and display custom data alongside search results.
Marimo is a reactive Python notebook environment and data science integrated development environment. It functions as a scripting tool that maintains state consistency by automatically tracking variable dependencies and re-executing downstream code blocks whenever upstream inputs are modified. The platform distinguishes itself by storing notebooks as standard, portable Python scripts rather than proprietary formats, ensuring compatibility with version control systems. It integrates artificial intelligence to assist with code generation and debugging based on the current execution context, whi
Integrates SQL database querying directly into the execution workflow for programmatic data manipulation.
This toolkit provides an asynchronous interface for interacting with relational databases, offering a unified driver-agnostic layer for managing connection pools and executing transactions. It is designed to integrate with asynchronous runtimes, enabling non-blocking database operations while maintaining secure, encrypted communication between the application and the database server. The project distinguishes itself through its compile-time validation capabilities, which use procedural macros to inspect SQL syntax and parameter types against a live database schema during the build process. Th
Provides a comprehensive asynchronous SQL toolkit featuring compile-time validation and type-safe row mapping.
This project is a native Go driver for the MySQL protocol, providing a communication layer that enables applications to interact with relational database management systems. It implements the standard database interface, allowing developers to manage persistent connections, execute queries, and handle transactions within their applications. The driver functions by translating high-level database commands into the specific binary packet format required for communication with MySQL servers. It manages network sessions through a connection pooling mechanism and supports context-aware query cance
Implements the standard database interface to facilitate structured data access and interaction with relational databases.
This project is a functional programming library and toolkit for building production TypeScript applications. It provides a system for managing concurrency, error handling, and resource lifecycles using functional effects. The project distinguishes itself through a comprehensive suite of specialized toolkits, including a dependency injection framework for decoupling service implementations, a workflow orchestrator for coordinating durable processes, and a SQL database toolkit for consistent data operations across multiple dialects. It also implements an OpenTelemetry instrumentation library f
Offers a type-safe SQL toolkit for executing data operations consistently across multiple database dialects.
SQLAlchemy is a comprehensive Python SQL toolkit and object-relational mapper that provides a full suite of tools for interacting with relational databases. It serves as a foundational layer for database connectivity, offering both a high-level object-oriented interface for data persistence and a programmatic SQL expression language for constructing complex, dialect-agnostic queries. The project distinguishes itself through its sophisticated unit of work persistence, which coordinates atomic transactions and tracks object state changes to minimize redundant database operations. It provides a
Provides a comprehensive library for interacting with relational databases using object-oriented patterns and a powerful SQL expression language.
Sea-ORM is an asynchronous SQL object-relational mapper and database toolkit for mapping relational tables to strongly typed objects. It provides a relational database mapper for performing CRUD operations across MySQL, PostgreSQL, and SQLite, and includes a programmatic dynamic query builder for constructing complex SQL statements. The project distinguishes itself by providing a GraphQL schema generator that transforms database entities into typed schemas with built-in pagination and filters. It also features a dedicated database migration tool for defining and applying versioned schema chan
Provides a comprehensive asynchronous SQL toolkit for type-safe mapping and query execution.
PyMySQL is a MySQL database connector and SQL database driver for Python environments. It serves as a client library that enables Python applications to establish network connections and interact with MySQL database servers. The library is a pure Python implementation of the MySQL client-server wire protocol. This design allows for MySQL integration and data management without requiring native C extensions. The project provides capabilities for database connectivity, query execution, and secure access control. It follows the DB-API 2.0 specification to provide a consistent interface for mana
Acts as a low-level interface for executing SQL queries and managing data transactions.
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.
Enables executing external machine learning model requests and text-to-SQL translations directly within standard database queries.
Dieses Projekt ist ein MySQL-Datenbanktreiber für Node.js, der Netzwerkverbindungen herstellt und SQL-Abfragen unter Verwendung eines nativen Kommunikationsprotokolls ausführt. Er fungiert als asynchroner SQL-Client und bietet eine auf Promises basierende Abfrageschnittstelle sowie Unterstützung für async/await-Muster zur Verwaltung nicht blockierender Datenbankoperationen. Die Bibliothek enthält eine vollständige Implementierung des MySQL-Protokolls und dient als Toolkit zum Erstellen benutzerdefinierter Datenbankserver, Proxys oder Clients. Sie fungiert zudem als Connection-Pool-Manager und Tool zur Injektionsprävention, wobei vorbereitete Anweisungen (Prepared Statements) und parametrisierte Abfragen verwendet werden, um Datenbankinteraktionen abzusichern. Das Projekt deckt ein breites Spektrum an Datenbankintegrationsfunktionen ab, einschließlich der Koordination atomarer Transaktionen, Binär-Log-Streaming und tabellarischem Daten-Streaming für Massenimporte. Es verwaltet Ressourcenlebenszyklen durch automatisierte Verbindungsbereinigung und bietet verschiedene Authentifizierungsmechanismen, wie Passwort-Hash-Authentifizierung und sichere Handshake-Aushandlung. Die Konnektivität wird zusätzlich durch SSL-Verschlüsselung, Komprimierung des Netzwerkverkehrs und die Fähigkeit unterstützt, Datenverkehr über benutzerdefinierte Duplex-Stream-Transporte zu leiten.
Provides a database interface with promise-based query execution and async/await support.
Connector-X is a high-performance SQL data extraction library and bridge for transferring relational database records into memory-efficient data structures. It functions as a parallel database connector and federated query engine capable of executing and joining queries across multiple remote database connections to aggregate data locally. The project distinguishes itself through a zero-copy approach to data loading, which transfers SQL query results into memory structures without duplicating data. It maximizes throughput by partitioning SQL queries into threads, employing parallel columnar a
Provides a parallel database connector that partitions SQL queries into threads to maximize extraction throughput.