Awesome GitHub RepositoriesSQL Database Connectivity

This project is a business intelligence suite and SQL data visualization platform used for data analysis, reporting, and monitoring. It provides a web application for exploring datasets and building interactive dashboards, complemented by a web-based SQL query editor for analyzing raw data from connected stores. The platform features a semantic data layer to define standardized metrics and dimensions, ensuring consistent data interpretation across reports. It includes a security framework with role-based access control to manage user permissions and authentication across shared dashboards. T

This project is a comprehensive technical reference and programming cheatsheet for the Python language. It serves as a curated catalog of language features, syntax patterns, and standard library functions designed to help developers identify and apply correct coding patterns. The documentation covers a broad range of functional areas, including language fundamentals such as object-oriented structuring, functional logic, and list comprehensions. It also provides guidance on utilizing the standard library for data analysis, file management, networking, and concurrent execution. The reference e

Cube is a semantic layer data platform that maps raw SQL databases to standardized business metrics and dimensions. It functions as a SQL dialect translator, converting abstract semantic queries into optimized SQL statements for various cloud data warehouses. The platform operates as a multi-tenant data gateway, isolating information and security permissions for different customers within a single deployment. It includes a relational caching engine that stores pre-aggregated query results to reduce latency and decrease the load on primary data warehouses. The system provides a REST-based int

StarRocks is a distributed SQL OLAP database engine designed for real-time analytics and high-performance multi-dimensional analysis. It functions as a data lakehouse query engine that enables SQL execution across large datasets and external open table formats without requiring local data imports. The system employs a shared-nothing distributed architecture and utilizes the MySQL protocol to integrate with business intelligence tools. It maintains real-time data consistency through a primary key upsert model and accelerates query response times using vectorized execution and cost-based optimi

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

pq is a PostgreSQL driver for Go that implements the standard database/sql interface. It serves as a connection library and protocol implementation that translates application data types into the binary and text formats required by PostgreSQL. The project provides specialized utilities for high-performance data ingestion using bulk data loading and a dedicated bulk data importer. It also features an implementation for listening to asynchronous server notifications and provides tools for connection load balancing across multiple hosts and ports. The driver covers a broad surface of database i

go-cloud is a toolkit of cloud-agnostic libraries that provide portable Go interfaces for interacting with common cloud services. It enables multi-cloud application development by decoupling business logic from specific provider API implementations. The project utilizes a driver-based system to map generic interface calls to vendor-specific requests. This allows applications to switch between different cloud backends for blob storage, relational databases, and asynchronous publish-subscribe messaging without changing the core application code. Beyond storage and messaging, the toolkit includ

Kanboard ist ein selbst gehostetes Kanban-Projektmanagement-Tool und eine Produktivitätssuite, die für die Verfolgung von Softwareaufgaben und Teamzusammenarbeit entwickelt wurde. Es bietet ein visuelles System zur Verwaltung von Arbeitsabläufen durch die Verwendung von Boards, Spalten und Karten. Das Projekt verfügt über ein erweiterbares Plugin-Framework und eine umfassende API für die programmatische Aufgaben- und Projektverwaltung. Es beinhaltet spezialisiertes Identitätsmanagement durch LDAP-Integration, was die Synchronisierung von Benutzerkonten und Gruppenberechtigungen von Verzeichnisservern ermöglicht. Das System deckt eine breite Palette von Funktionen ab, einschließlich ereignisgesteuerter Workflow-Automatisierung, detaillierter Projektanalysen wie Burn-Down-Diagrammen und Zykluszeitmessung sowie granularer rollenbasierter Zugriffskontrolle. Es unterstützt zudem integrierte Zeiterfassung, Unteraufgaben-Zerlegung und Multi-Methoden-Authentifizierung, einschließlich Zwei-Faktor-Authentifizierung und Reverse-Proxy-Unterstützung. Die Anwendung ist mit MySQL und PostgreSQL für die persistente Datenspeicherung kompatibel und kann mittels Docker Compose bereitgestellt werden.

go-admin is a framework for generating administrative interfaces and data visualization dashboards using the Go programming language. It functions as a low-code dashboard builder and a web-based interface for performing create, read, update, and delete operations across multiple SQL database dialects. The project features a deployment model that compiles backend logic and frontend assets into a single executable binary for simplified distribution. It includes a role-based access control system to manage user permissions and restrict administrative functions based on assigned roles. The frame

VisiData is a terminal-based interactive data analysis tool and browser designed for exploring, filtering, and sorting large tabular datasets. It functions as a structured data inspector that loads and flattens complex formats like JSON, XML, and PCAP into interactive sheets, as well as a terminal file manager for navigating directories and performing staged filesystem operations. The project distinguishes itself by rendering data visualizations, such as scatter plots and histograms, directly in the terminal using Unicode Braille characters. It provides a Python-based data wrangling environme

Eve is a REST API framework that maps database collections to web resources through declarative configuration files. It functions as a database-to-API mapper, automatically exposing data as RESTful endpoints with built-in support for CRUD operations and schema-based request validation. The project distinguishes itself through a HATEOAS API engine that generates hypermedia links and resource schemas for dynamic client discovery. It also includes an automated Swagger documentation generator that produces interactive specifications for client SDK generation and testing. The framework provides a

This is a Backend as a Service SDK for Apple platforms, providing a collection of libraries that connect iOS and macOS applications to cloud databases, authentication services, and serverless infrastructure. It serves as a developer kit for integrating real-time data synchronization, file storage, and push notifications into native apps. The SDK is distinguished by its generative AI integration, which routes text and multimodal prompts between on-device models and cloud-hosted large language models. It further differentiates itself with a specialized app distribution tool for managing pre-rel

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

Maddy is a modular mail server that assembles a complete email system by connecting small, single-purpose modules through a declarative configuration file. Rather than a monolithic stack, it lets operators compose message processing, storage, authentication, and security enforcement from interchangeable building blocks, with each module handling a specific function like receiving SMTP connections, verifying credentials, or applying policy checks. The server distinguishes itself through its flexible authentication and security architecture. It delegates user verification to external systems in

dlt ist ein Python-Tool zur Datenaufnahme und ein ETL-Pipeline-Framework, das darauf ausgelegt ist, Daten aus verschiedenen Quellen abzurufen und in strukturierten Zielen zu speichern. Es fungiert als Schema-Inferenz-Engine, die automatisch Datentypen erkennt und verschachtelte JSON-Strukturen in relationale Tabellen flacht, wobei Daten von Quellen in Lakehouses, Warehouses oder Vektordatenbanken verschoben werden. Das Projekt zeichnet sich durch KI-gestützte Pipeline-Generierung aus, die Large Language Models nutzt, um Extraktionscode und Konnektoren für REST-APIs zu erstellen. Es unterstützt zudem multimodale Vektorspeicherung und die spezialisierte Befüllung von Vektordatenbanken zur Unterstützung von KI- und Machine-Learning-Anwendungen. Das Framework deckt ein breites Spektrum an Funktionen ab, einschließlich automatisierter Schema-Evolution, inkrementellem Datenladen mittels Statusverfolgung und Datenqualitätsvalidierung durch die Durchsetzung von Datenverträgen. Es bietet Tools für relationale Datennormalisierung, Pre- und Post-Load-Transformationen sowie eine Vielzahl von Ziel-Adaptern für SQL-Datenbanken und Cloud-Objektspeicher. Die Observability wird durch Pipeline-Ausführungs-Dashboards, Spalten-Lineage-Tracking und Schema-Versionsverifizierung mittels inhaltsbasierter Hashes gehandhabt.

This project is a comprehensive collection of Python programming education materials, including tutorials, exercises, and curated code samples. It serves as a learning curriculum and software engineering toolkit, utilizing Jupyter Notebooks to combine executable code with descriptive educational text. The repository provides practical implementation guides for building large language model applications, such as retrieval-augmented generation systems, stateful AI agents, and machine learning workflows. It distinguishes itself by offering a structured approach to agentic coding workflows, cover

dplyr is an R data manipulation library that provides a grammar for transforming tabular data frames. It functions as an in-memory data frame processor and a relational data algebra tool, using a consistent set of verbs to filter, select, and summarize data. The project includes a SQL translation engine that converts high-level data manipulation expressions into optimized queries. This allows users to perform transformations directly on remote relational databases and cloud storage without pulling data locally. The library covers a broad range of tabular operations, including column mutation

Sequel is a relational database toolkit for Ruby that provides object-relational mapping, a fluent SQL query builder, and schema migration capabilities. It maps database tables to Ruby classes with support for associations, validations, lifecycle hooks, and eager loading, offering a comprehensive ORM layer for building data-centric applications. Sequel distinguishes itself through a plugin-based extension architecture that allows composable customization of models, databases, and datasets without relying on deep inheritance hierarchies. It includes a thread-safe connection pool with support f

Flask-AppBuilder ist ein Rapid-Application-Framework auf Basis von Flask, das die Erstellung von Admin-Interfaces und datenbankgesteuerten Anwendungen automatisiert. Es fungiert als automatischer CRUD-Generator und SQL-Datenbank-Admin-Interface, das die Generierung von Benutzeroberflächen und REST-APIs direkt aus Datenmodellen ermöglicht. Das Framework enthält ein Sicherheitssystem zur Verwaltung von Benutzeridentitäten und Zugriffsrollen durch rollenbasierte Zugriffskontrolle (RBAC). Es unterstützt die Authentifizierung über interne Datenbanken oder externe Anbieter wie LDAP, OAuth und OpenID. Die Plattform deckt breitere Funktionen ab, einschließlich Multi-Dialekt-Datenbankkonnektivität, Modell-Audit-Tracking und Internationalisierung von Benutzeroberflächeninhalten. Zudem bietet sie Tools zur Datenvisualisierung durch Diagramme, Dateiupload-Handling und dynamische Menügenerierung basierend auf Benutzerberechtigungen.

Redka ist ein SQL-basierter Key-Value-Store, der eine Redis-kompatible Schnittstelle implementiert. Er fungiert als relationale Datenbrücke, die nicht-relationale Protokollbefehle in relationale Abfragen übersetzt, um Persistenz und ACID-Transaktionen unter Verwendung eines SQL-Datenbank-Backends bereitzustellen. Das System ermöglicht die relationale Datenintrospektion, indem es interne Key-Value-Daten als SQL-Views offenlegt, was direkte Abfragen und Analysen mittels relationaler Syntax ermöglicht. Es kann als eigenständiger Netzwerkserver oder als eingebettete Bibliothek innerhalb einer Go-Anwendung bereitgestellt werden. Das Projekt unterstützt eine Vielzahl von Datenstrukturen, einschließlich Strings, Listen, Hashes, ungeordneten Sets und sortierten Sets. Es bietet Funktionen für das Key-Lifecycle-Management mit Time-to-Live-Metadaten, atomare numerische Operationen und Set-Algebra. Zur Verwaltung von Performance und Zugriff enthält es einen In-Memory-Speichermodus und einen Read-Only-Verbindungsmodus.