7 个仓库
Standardizes database operations by enforcing a consistent interface for entity persistence and retrieval.
Distinct from Data Persistence: Focuses on architectural contracts for persistence rather than general data persistence.
Explore 7 awesome GitHub repositories matching data & databases · Data Access Contracts. Refine with filters or upvote what's useful.
This project is a TypeScript-based architectural framework designed to implement domain-driven design and hexagonal architecture in enterprise applications. It provides a structured boilerplate that isolates core business logic from infrastructure concerns, ensuring that domain entities, use cases, and external technology adapters remain decoupled and maintainable. The framework distinguishes itself by enforcing strict architectural boundaries and dependency inversion, preventing unauthorized access to core logic from external layers. It utilizes a command-query responsibility segregation pat
Standardizes database operations by enforcing a consistent interface for entity persistence and retrieval across different modules.
OpenMetadata is an enterprise data catalog, metadata platform, and governance suite that functions as a knowledge graph for data assets. It serves as an AI-ready metadata layer, providing governed context and organizational memory to large language model agents via the Model Context Protocol. The platform distinguishes itself by capturing institutional knowledge, linking conversations, decisions, and remediation notes directly to data assets to preserve tribal knowledge. It integrates AI agents to automate metadata governance, such as suggesting descriptions and identifying sensitive data thr
Implements formal agreements between data producers and consumers to enforce schema expectations and quality SLAs.
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
Defines explicit schemas and expectations for data models to prevent breaking changes from propagating to downstream consumers.
DataHub is a metadata management platform designed to unify technical, operational, and business context across diverse data ecosystems. By utilizing a graph-based metadata model and an event-driven ingestion architecture, it creates a centralized source of truth that maps complex data relationships, lineage, and ownership. This foundational framework enables organizations to maintain a synchronized view of their data landscape, supporting both human-led discovery and automated data operations. The platform distinguishes itself through its focus on grounding artificial intelligence and autono
Establishes formal agreements between data producers and consumers to define expected data structure and reliability standards.
eShopOnWeb is a reference application for ASP.NET Core that demonstrates a sample e-commerce site. It serves as a template for building scalable services using domain-driven design to separate business logic from infrastructure and data access. The project implements a decoupled messaging pattern through a request pipeline to separate web controllers from application logic. It utilizes a repository pattern to abstract data persistence and isolate the core application logic from the specific database storage mechanism. The application covers a broad surface of web capabilities, including user
Enforces consistent interfaces for entity persistence and retrieval through defined data access contracts.
dlt 是一个 Python 数据摄取工具和 ETL 流水线框架,旨在从不同来源获取数据并将其持久化到结构化目标中。它作为一个模式推断引擎,可自动检测数据类型并将嵌套的 JSON 结构扁平化为关系表,将数据从源端移动到数据湖、数据仓库或向量数据库。 该项目通过 AI 驱动的流水线生成脱颖而出,利用大语言模型为 REST API 构建提取代码和连接器。它还支持多模态向量存储和向量数据库的专门填充,以支持 AI 和机器学习应用。 该框架涵盖了广泛的功能,包括自动化模式演进、通过状态跟踪进行增量数据加载,以及通过强制执行数据契约进行数据质量验证。它提供了用于关系数据规范化、加载前后转换的工具,以及针对 SQL 数据库和云对象存储的多种目标适配器。 可观测性通过流水线执行仪表板、列血缘跟踪以及使用基于内容的哈希进行模式版本验证来处理。
Enforces data contracts and quality standards to ensure the integrity and accuracy of loaded datasets.
本项目是一个 Laravel 的数据库抽象层,实现了存储库模式以将业务逻辑与 Eloquent 数据库查询解耦。它提供了一个用于数据检索、分页和过滤的标准接口。 该系统包括一个查询标准机制,用于根据请求参数应用可重用的搜索条件,以及一个在记录创建、更新或删除期间自动清除存储结果的缓存包装器。它还具有一个展示层,用于将原始数据库模型属性转换为用户界面的格式化输出。 其他功能包括用于脚手架模型、存储库、控制器和服务提供商的命令行工具,以及用于验证存储库数据和转换模型属性的工具。
Enforces a strict interface contract for data operations to ensure interchangeable persistence layer implementations.