7 Repos
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 ist ein Ruby-Objekt-Serializer, der darauf ausgelegt ist, komplexe Backend-Datenobjekte in strukturierte JSON-Repräsentationen zu transformieren. Er implementiert spezifisch das JSON:API-Format, um einen konsistenten Datenaustausch zwischen Servern und Clients zu gewährleisten. Die Bibliothek fungiert als Generator für zusammengesetzte Dokumente, der es ermöglicht, verwandte Ressourcen in eine einzige Antwort einzubetten, um Netzwerkanfragen zu minimieren. Sie verwendet eine klassenbasierte Schemadefinition, um interne Datenbankmodelle von der öffentlichen API-Repräsentation zu entkoppeln. Das Projekt enthält ein Command-Line-Tool zur Generierung von Serializer-Boilerplate durch Scannen von Datenbankschemata. Die Performance wird durch schlüsselbasiertes Ausgabe-Caching und Instrumentierungs-Tools verwaltet, die die Ausführungslatenz der Serialisierungs- und Encoding-Prozesse verfolgen.
Generates compound documents by embedding related resources in a flat structure within a single JSON response.
MongoEngine ist ein Python-Object-Document-Mapper, der Datenbankeinträge in Objekte übersetzt, um eine objektorientierte Schnittstelle für die Datenpersistenz bereitzustellen. Er dient als Dokument-Manager und Schema-Validator für MongoDB und bildet Klassen auf Dokumente ab, um Datentypen und Validierungsregeln durchzusetzen. Das Projekt bietet ein Lazy-Loaded-Queryset-System zum Filtern, Sortieren und Aggregieren von Sammlungen unter Verwendung einer Python-Syntax. Es verwaltet komplexe Datenstrukturen durch Funktionen wie Dokumentenvererbung, rekursive Handhabung eingebetteter Dokumente und referenzbasierte Objektverknüpfung. Die Bibliothek deckt breite Funktionen ab, einschließlich Schema-Migration, Volltextsuche und die Verwaltung großer Binärdateien über das GridFS-Dateisystem. Sie enthält zudem Tools zur Optimierung von Datenbankindizes, zur Profilierung der Abfrageleistung und signalbasierte Lifecycle-Hooks, um Logik während Dokumentenereignissen zu automatisieren.
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.