17 repositorios
Interfaces for executing queries that span multiple connected data sources.
Distinct from Data Querying: Distinct from Data Querying: focuses on multi-source join capabilities rather than single-source retrieval.
Explore 17 awesome GitHub repositories matching data & databases · Cross-Source Querying. Refine with filters or upvote what's useful.
This repository serves as a comprehensive research platform and toolkit for advancing machine learning, quantum computing, and large-scale scientific data analysis. It provides foundational frameworks for developing complex algorithmic systems, offering the necessary infrastructure for distributed training, computational graph execution, and high-performance model development. The project distinguishes itself by integrating specialized research domains with robust, privacy-preserving methodologies. It supports diverse scientific discovery through tools for quantum simulation, physics-informed
Provides cross-corpora query routing to identify and select relevant data sources for complex multi-step analysis.
DataEase is an open-source, self-hosted business intelligence platform designed for building interactive data visualizations and managing analytical reporting. It provides a centralized environment where users can construct dashboards through a drag-and-drop interface, connecting to diverse data sources including relational databases, data warehouses, and external APIs. The platform distinguishes itself through its focus on embedded analytics and enterprise-grade governance. It allows for the seamless integration of charts, dashboards, and management modules into third-party web applications
Executes data queries that span different connected sources for unified analysis.
This project is a Python-based framework that functions as a generative AI agent for programmatic data analysis. It enables users to interact with structured data sources through natural language prompts, translating these requests into executable code to perform analysis, data cleaning, and visualization. By maintaining conversational context across multi-turn interactions, the system allows for iterative exploration and the building of complex data narratives. The framework distinguishes itself through a robust semantic layer and secure execution model. It maps raw datasets to descriptive m
Provides interfaces for executing queries that span multiple connected data sources.
Airbyte is a data integration platform designed to synchronize information between diverse applications, databases, and data warehouses. It functions as an extract, transform, and load orchestrator that manages automated data movement workflows across cloud, on-premise, and hybrid environments. The platform provides a standardized interface for connectors, enabling the movement of structured and unstructured data while maintaining stateful checkpoints for reliable incremental syncing. The platform distinguishes itself through a containerized architecture that isolates connectors to prevent de
Aggregates and retrieves records from multiple connected applications to provide unified context.
Mihon is a content aggregation client and manga reader application designed to manage digital comic libraries. It provides a centralized interface for organizing personal collections and tracking reading progress across various series. The application distinguishes itself through a modular architecture that supports dynamic extension loading, allowing users to integrate third-party content sources directly into the interface. It enables aggregated content discovery by executing concurrent searches across multiple providers, consolidating results into a unified view. Beyond basic reading, the
Queries several connected content providers simultaneously to locate specific series without browsing each source individually.
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
Executes SQL queries against external databases by mapping remote tables to local schemas for unified analysis.
dbt-core is a command-line framework for transforming data within a warehouse using modular SQL and version control. It functions as a data transformation engine that enables users to define data structures and business logic through declarative configuration files, which the system then compiles into executable code. By managing complex data dependencies through a directed acyclic graph, it ensures that transformation tasks execute in the correct order while maintaining a manifest-driven state to track lineage and execution history. The project distinguishes itself through an adapter-based d
Enables querying across multiple databases within a single cluster to simplify complex data modeling tasks.
This project is a centralized repository of plugins designed to integrate diverse external manga sources into a single reading interface. It functions as a content aggregation system that allows users to browse and access digital comics from multiple online platforms through a unified application. The system utilizes a framework of web scrapers that normalize data from various websites into a consistent viewing format. To manage these integrations, the project employs a background synchronization service that performs automated version checks, ensuring that installed plugins remain compatible
Transforms search queries to reconcile naming and regional variations across multiple connected content sources.
Scira is an AI-powered search and synthesis engine that uses agentic research workflows to find and organize information from the web and academic sources. The system breaks complex queries into multi-step plans and generates grounded answers with inline citations for verification. The platform distinguishes itself by executing Python code within isolated sandboxes to perform data analysis and create visual charts from retrieved data. It also implements retrieval-augmented generation to perform semantic searches across uploaded documents, including PDFs and CSV files, and integrates with clou
Executes queries across the open web, social media, and code repositories using specialized scrapers.
This project is a metadata query engine and indexer for markdown files, designed to transform YAML frontmatter and inline fields into dynamic tables and lists. It provides a background process that extracts tags and custom fields into a searchable database, enabling the automated indexing of notes. The system is distinguished by its dual approach to data retrieval: a dedicated query language for SQL-like filtering and grouping, and a JavaScript data API. This API allows for programmatic metadata extraction and the creation of custom views and extensions using TypeScript typings. Its broader
Uses logical operators to intersect or union multiple source filters for precise metadata extraction.
AlaSQL is a JavaScript SQL database engine that allows for the filtering, grouping, and joining of in-memory object arrays and JSON data. It functions as an in-memory SQL database and client-side data processor, enabling the execution of SQL statements against JavaScript arrays and external data sources in both browser and server environments. The project serves as a universal data query tool capable of performing relational joins across diverse sources, such as merging Google Spreadsheets, SQLite files, and remote APIs into a single result set. It also acts as an IndexedDB SQL wrapper, allow
Enables the execution of SQL queries that span and join data from multiple remote sources, including cloud spreadsheets.
Obsidian Copilot is an AI assistant plugin for Obsidian that brings conversational AI directly into your note-taking vault. It allows you to chat with multiple large language models, create and execute custom prompts, and edit notes through natural conversation, all without leaving your workspace. The plugin distinguishes itself by offering complete model flexibility, supporting OpenAI, Anthropic, Google, local, and self-hosted models with no vendor lock-in. It stores all chat history, system prompts, and custom commands as plain Markdown files in your vault, ensuring full data ownership and
Queries and synthesizes insights from webpages, videos, images, PDFs, and EPUBs via chat.
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
Executes unified queries across real-time and offline data segments with automatic time boundary management.
Calcite es un framework para analizar, optimizar y traducir consultas SQL a álgebra relacional para su ejecución en diversas fuentes de datos. Funciona como un motor de consultas entre fuentes, una librería de análisis SQL y un optimizador de álgebra relacional. El proyecto proporciona un motor de optimización basado en costos que transforma planes de consulta lógicos en planes de ejecución física eficientes mediante reglas conectables. Utiliza adaptadores de traducción para convertir solicitudes SQL estándar a los formatos nativos de bases de datos externas y sistemas de mensajería, permitiendo la federación de datos entre sistemas de almacenamiento heterogéneos. El sistema cubre el ciclo de vida completo de la consulta, incluyendo el análisis y validación de SQL frente a esquemas, la traducción de expresiones a operadores algebraicos y la selección de planes de ejecución eficientes. También incluye una interfaz de línea de comandos para ejecutar consultas y gestionar conexiones a fuentes de datos.
Implements a query engine that retrieves and processes data from multiple heterogeneous backend storage systems using a unified SQL dialect.
Television is a terminal-based search launcher that provides real-time fuzzy matching across multiple data sources, including files, git repositories, environment variables, shell history, and custom user-defined channels. It presents a multi-panel terminal interface where search results, previews, and input are displayed simultaneously, with a frecency-based ranking engine that combines match quality with the frequency and recency of past selections to surface the most relevant entries. The project is built around a declarative, TOML-driven architecture where search channels, previews, and a
Queries and filters across files, git repositories, and environment variables from a single terminal interface.
Chartbrew is a self-hosted business intelligence platform and data visualization engine designed to transform raw data from SQL databases and external API endpoints into interactive charts and dashboards. It serves as a tool for building analytics dashboards that monitor business metrics and KPIs through a privately hosted environment. The platform distinguishes itself with an embedded analytics workflow, allowing users to generate secure, time-limited shared links and iframes to display private charts on external websites. It also provides programmatic chart generation via API and integrates
Executes queries against external SQL databases and API endpoints to retrieve data for visualization.
Gravitino is a federated metadata lake and unified data catalog designed to manage tables, files, and AI models across diverse data sources and cloud storage. It serves as a centralized interface for governing schemas, access controls, and tagging across relational databases, messaging queues, and object stores. The project distinguishes itself by unifying the management of AI assets, such as machine learning models and their version lineages, alongside traditional tabular data. It also implements the Iceberg REST specification to provide a standardized metadata server and proxy for lakehouse
Executes single SQL queries that join datasets across different data stacks and diverse sources.