# alldatacenter/alldata

🔥🔥 AllData可定义数据中台，以数据平台为底座，以数据中台为桥梁，以机器学习平台为工厂，以大模型应用为上游产品，提供全链路数字化解决方案。产品正式演示体验、社群咨询、商务采购：https://docs.qq.com/doc/DVHlkSEtvVXVCdEFo

Repository: https://github.com/alldatacenter/alldata
Canonical: https://ross.abutalabs.com/products/alldata
Homepage: http://www.aolingdata.com
Language: Java
License: GPL-3.0
License Family: copyleft
Topics: paimon, datart, dinky, streampark, cube-studio, datasophon, cloudeon, dolphinscheduler, datax, seatunnel, supersonic, tis, amoro, bisheng, chat2db, dbswitch, datavines, gravitino, openmetadata, sqlrest
Last push: 2026-07-16T04:04:25+00:00

## Health v2 (maintenance only)
Score: 83/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 92, release rhythm 61, longevity 100
- inputs: {"age_days": 2522, "days_push": 48, "days_rel": 49, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3082, forks 978 (observed 2026-08-28T04:07:41.929981+00:00)

## What it is
AllData is a definable data platform (数据中台) that integrates open-source components like DolphinScheduler, DataX, SeaTunnel, OpenMetadata, and Datavines into a unified full-stack data solution. It combines a data platform foundation, data middle-platform bridge, machine learning platform, and LLM application layer for end-to-end digital transformation.

## Use cases
- build an enterprise data middle platform
- sync data between heterogeneous databases
- orchestrate batch and streaming ETL pipelines
- manage data sources and metadata centrally
- monitor data quality across the warehouse
- deploy machine learning workflows on a unified platform
- self-host an integrated big data toolchain

## When to choose
- you need an integrated suite of data integration, scheduling, metadata, and quality tools under one UI
- your team wants a self-hosted alternative to commercial data platforms
- you are building a full data platform from proven open-source components

## When to avoid
- you need only a single lightweight tool for one specific task
- you require permissive licensing (it is GPL-3.0)
- you cannot operate a complex multi-component Java deployment

## Facets
- artifact type: application
- maturity: active
- function: etl, data-science, workflow-automation, database, analytics, machine-learning, chatbot
- domain: big-data, analytics, self-hosted, machine-learning
- platform: self-hosted, jvm
- tags: data-mesh, data-platform, lakehouse, metadata-management, data-quality, open-source-stack, chinese, data-engineering, docker, web-server

## Member repositories
- alldatacenter/alldata (main) score 83

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:41.929981+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:27:42.563400+00:00, confidence not recorded.
  - readme: https://github.com/alldatacenter/alldata (fetched 2026-08-28T04:07:41.929981+00:00, sha 147e3909d907)
  - homepage: http://www.aolingdata.com (fetched 2026-08-29T09:42:56.887097+00:00, sha 1627df90e609)
- Data as of 2026-08-30T08:39:29.467469+00:00.