qData-mdm:基于 Spring Boot 和 Vue 3 的主数据管理平台项目

📖简体中文 | 📖English | 📖日本語

Platform Overview

qData Master Data Platform helps organizations manage master data for customers, suppliers, materials, and organizational units. Teams define models by business domain and match records from different systems that refer to the same entity. Once merged records pass quality checks and receive approval, they become authoritative. Downstream systems can receive the same data through distribution tasks or retrieve it through query APIs. Source records and change history show where each master record came from and how it has changed.

✨✨✨Online Documentation✨✨✨ https://qdata.qiantong.tech

✨✨✨Open-Source Edition Demo✨✨✨ https://demo-mdm.qdata.tech (username qData, password qData123).

✨✨✨Professional Edition Demo✨✨✨ https://pro-demo-mdm.qdata.tech. Please contact customer service to obtain a demo account.

If qData-mdm helps you, give the project a star ⭐️ to support its development.

Feature List

Module	Components	What you can do
Dashboard	Dashboard	See totals for master records, models, domains, reference items, and active grants within your permissions. Compare record counts by domain and lifecycle state, drill into changes that took effect in the last 7 or 30 days, and follow up on failed publications or expiring grants.
Master data management	Authoritative records, my requests, data entry tasks, task center	Create, edit, copy, import, and export records under a published model. Bulk changes pass validation and take effect as a single batch. Manage active, frozen, inactive, and archived records; compare versions and request a restore. Track or withdraw your requests and handle approvals, data entry, and remediation in the task center.
Model management	Domains, model catalog, models, hierarchies and relationships, reference data, coding schemes	Organize standard and classification models by domain and folder. Define fields, model references, and one-to-many submodels; inspect dependencies in the relationship graph. Bind fields to reference values or codes built from multiple segments. Publish manually after validation and approval to create the physical schema. Revisions retain history and undergo compatibility checks.
Rule management	Matching, survivorship, quality rules	Find duplicate candidates with exact, normalized exact, fuzzy, or weighted multi-field matching. Select field values by source priority, trust score, recency, or preference for non-empty values. Define checks for required values, format, range, uniqueness, reference values, and relationships between fields.
Workflow management	Workflow configuration, workflow instances	Route models, record edits, lifecycle changes, and merge results for approval. See the current step, assignee, comments, and decision history. Approved models still require manual publication; approved record changes and merge results take effect according to business rules.
Data ingestion	Source systems, ingestion tasks, source records	Read databases in full or incrementally, import CSV/XLS/XLSX files, or pull from external APIs. Identify records by source key and map incoming fields to the model. Unchanged records are skipped; changed records get a new source version. Inspect failures by run.
Multi-source consolidation	Duplicate detection, match review, merge management	Review match scores and evidence to confirm, split, or defer candidate groups. Confirm single records individually or resolve conflicting values field by field, retaining their sources. Results must pass quality checks and approval before they create or update authoritative records.
Data quality	Quality tasks, issue records, remediation tasks	Check authoritative records manually or on a schedule. Group failures by record, inspect the rule, field, and cause, and assign individual issues for correction. A later passing check marks the item resolved; an administrator confirms closure of the issue record.
Data distribution	Target systems, distribution tasks, data services	Set the record scope, field mappings, and schedule for each target API. Push full or incremental updates, including lifecycle changes for previously distributed records. Publish read-only REST services for lookup by master record ID or filtered, paginated queries.
Access management	Data grants, service grants	Grant row, field, and operation permissions by user, role, or organization. Inspect effective access and see which grants provide it. Authorize published APIs separately by calling user or client, service, and validity period.
Audit and traceability	Operation audit, change history, data versions, source tracing	Inspect records affected by successful operations, search changes across models, and compare any two official versions. Follow current and historical mappings from an authoritative record to manual entries or external source records and their associated approvals.
System administration	Users, roles, menus, departments, positions, dictionaries, settings, notices, logs	Manage accounts and the organization hierarchy. Use roles to control menu, button, and data access. Maintain shared lookup values and runtime settings, publish notices, and search operation and system logs.

💡 Have a suggestion or feature request? Open an issue.

Technology Stack

qData-mdm separates the Spring Boot backend from the Vue 3 frontend and integrates authentication, database access, caching, and UI components.

Category	Technology	Purpose
Backend	Spring Boot	Application framework for rapid development and consistent startup
	Spring Security	User authentication, authorization, and security controls
	MySQL, DM8	Persistent storage and data source configuration
	MyBatis-Plus	Database access and multiple data sources
	Redis	Caching, session state, and middleware
	Knife4j / OpenAPI	API documentation and integration testing
Frontend	Vue 3	Reactive frontend framework
	Element Plus	UI components for the admin interface
	Vite	Development and build tooling
Third-party libraries	AntV X6	Workflow diagrams, visual design, and interaction
	ECharts	Charts and data visualization

Commercial Licensing

qData-mdm provides two editions: Professional Edition and Open-Source Edition, meeting user needs across different scales and scenarios. Each has its own focus while complementing the other: the Open-Source Edition helps users get started at low cost, while the Professional Edition provides greater depth and support. Whichever edition you choose, qData-mdm aims to be a reliable partner that helps enterprises unlock data value and accelerate digital transformation.

👉 For Open-Source Edition brand authorization or Professional Edition consultation, see 💼 Licensing Details.

Quick Start

1. Online Demo

• Sign in to the Community Open-Source Edition demo to explore the main features without installing anything.

2. Choose a Deployment Method

• Local deployment. Use the Docker Compose configuration in deploy/docker/ to start the full environment locally.
• Run from source. Start the qdata-mdm-server backend and qdata-mdm-ui frontend separately for development and integration testing.
• Self-managed deployment. Install, configure, and manage the services manually for production or custom environments.

Deployment Environment

Install the following prerequisites before deploying qData-mdm.

Environment	Component	Recommended version	Notes
Backend	JDK	1.8 or later	OpenJDK 8 recommended
	Maven	3.6+	Build and dependency management
	DM8 / MySQL	8.0+	Relational database. Development configuration defaults to DM8.
	Redis	5.0+	Caching and session state
	Docker / Docker Compose	Optional	Quick evaluation and test deployments
	Operating system	Windows / Linux / Mac	All listed systems are supported
Frontend	Node.js	16+	Frontend build tooling
	npm	8+	Package manager
	Chrome / Edge	Latest	Recommended for local debugging and access

QQ Community

Join the official qData QQ community for updates, technical support, and discussions.

👉 Join the QQ community

System Screenshots

The screenshots show the Simplified Chinese interface.