7 repositorios
Techniques for nesting related data within parent documents.
Distinguishing note: Focuses on denormalization and nesting strategies.
Explore 7 awesome GitHub repositories matching data & databases · Document Embedding. Refine with filters or upvote what's useful.
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
RethinkDB models one-to-many relationships by nesting related data directly within a parent document to simplify retrieval and ensure atomic updates for smaller datasets.
JSON API is a set of industry standards for RESTful APIs that defines uniform protocols for resource serialization, error responses, and query parameters. It provides a specification for request and response payloads in JSON-based APIs to ensure consistency across endpoints. The specification focuses on reducing network requests through a structured resource serialization format and a standardized mechanism for embedding related resources into a single response. It utilizes a custom JSON media type for content negotiation and supports the definition of custom profiles to provide specialized i
Includes related resources alongside primary data in a single response using a reserved includes parameter.
This project is a MongoDB database driver and object-relational mapper that brings MongoDB support to the Laravel Eloquent model and query builder. It provides a NoSQL model mapper that allows MongoDB collections to be mapped to object-oriented models using the Active Record pattern. The integration enables the use of a fluent query builder for constructing queries and aggregation pipelines without writing raw database syntax. It supports schema-less model integration, allowing applications to manage unstructured data while maintaining compatibility with standard object-oriented patterns. Th
Supports storing related data directly within parent documents to reduce read lookups.
NPOI is a pure .NET library for reading and writing Microsoft Office files in both legacy binary (.xls) and modern OpenXML (.xlsx, .docx) formats, operating entirely without requiring Microsoft Office or COM interop. It runs on Windows and Linux under .NET Standard and .NET Framework runtimes, using only managed code to parse and generate Office documents. The library provides comprehensive spreadsheet capabilities, including creating, editing, and reading Excel workbooks in both .xls and .xlsx formats, with support for cell formatting, styles, and formulas. It includes a streaming row-by-row
Opens legacy .xls files by reading OLE2 compound storage structures.
fast_jsonapi es un serializador de objetos de Ruby diseñado para transformar objetos de datos de backend complejos en representaciones JSON estructuradas. Implementa específicamente el formato JSON:API para garantizar un intercambio de datos coherente entre servidores y clientes. La biblioteca funciona como un generador de documentos compuestos, permitiendo que los recursos relacionados se incrusten dentro de una única respuesta para minimizar las solicitudes de red. Utiliza una definición de esquema basada en clases para desacoplar los modelos de base de datos internos de la representación de la API pública. El proyecto incluye una herramienta de línea de comandos para generar boilerplate de serializador escaneando esquemas de base de datos. El rendimiento se gestiona mediante caché de salida basada en claves y herramientas de instrumentación que rastrean la latencia de ejecución de los procesos de serialización y codificación.
Generates compound documents by embedding related resources in a flat structure within a single JSON response.
MongoEngine es un mapeador de objetos-documentos (ODM) para Python que traduce registros de base de datos en objetos para proporcionar una interfaz orientada a objetos para la persistencia de datos. Sirve como gestor de documentos y validador de esquemas para MongoDB, mapeando clases a documentos para imponer tipos de datos y reglas de validación. El proyecto proporciona un sistema de queryset de carga perezosa (lazy-loaded) para filtrar, ordenar y agregar colecciones utilizando sintaxis Pythonica. Gestiona estructuras de datos complejas a través de características como la herencia de documentos, el manejo recursivo de documentos incrustados y la vinculación de objetos basada en referencias. La librería cubre amplias capacidades, incluyendo migración de esquemas, búsqueda de texto completo y la gestión de archivos binarios grandes a través del sistema de archivos GridFS. También incluye herramientas para la optimización de índices de base de datos, perfilado del rendimiento de consultas y hooks de ciclo de vida basados en señales para automatizar la lógica durante los eventos de documentos.
Supports nesting related data structures by treating embedded documents as dependent objects within a parent document.
python-docx-template is a template engine for generating Microsoft Word documents by merging .docx files with data contexts using a logic-based markup syntax. It functions as a document automator that injects variables, images, and sub-documents into Word files while maintaining the original styling. The project uses a rendering system based on Jinja2 to apply template logic and filters to Office Open XML files. It allows for the creation of custom template filters to transform data during the rendering phase and includes a command line interface for producing documents by passing a template
Inserts the contents of another file or programmatically generated document into a template variable.