diff --git a/README.md b/README.md index 30c121266d21ca..cd46248dc22d78 100644 --- a/README.md +++ b/README.md @@ -51,52 +51,96 @@ HOSTED_DOCS_ONLY--> ### 🏠 Docs: [docs.datahub.com](https://docs.datahub.com/) [Quickstart](https://docs.datahub.com/docs/quickstart) | -[Features](https://docs.datahub.com/docs/features) | -[Roadmap](https://feature-requests.datahubproject.io/roadmap) | -[Adoption](#adoption) | +[Features](https://datahub.com/products/) | +[Adoption](https://datahub.com/resources/?2004611554=dh-stories) | [Demo](https://demo.datahub.com/) | [Town Hall](https://docs.datahub.com/docs/townhalls) ---- -> 📣 DataHub Town Hall is the 4th Thursday at 9am US PT of every month - [add it to your calendar!](https://lu.ma/datahubevents/) -> -> - Town-hall Zoom link: [zoom.datahubproject.io](https://zoom.datahubproject.io) -> - [Meeting details](docs/townhalls.md) & [past recordings](docs/townhall-history.md) +## What is DataHub? -> ✨ DataHub Community Highlights: -> -> - Read our Monthly Project Updates [here](https://medium.com/datahub-project/tagged/project-updates). -> - Bringing The Power Of The DataHub Real-Time Metadata Graph To Everyone At DataHub: [Data Engineering Podcast](https://www.dataengineeringpodcast.com/acryl-data-datahub-metadata-graph-episode-230/) -> - Check out our most-read blog post, [DataHub: Popular Metadata Architectures Explained](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained) @ LinkedIn Engineering Blog. -> - Join us on [Slack](docs/slack.md)! Ask questions and keep up with the latest announcements. -## Introduction +**DataHub is an open-source metadata platform** that enables data discovery, observability, and governance across your entire data stack. Built by LinkedIn and proven at scale (100,000+ datasets), DataHub provides a unified catalog where teams can find, understand, and trust their data. -DataHub is an open-source data catalog for the modern data stack. Read about the architectures of different metadata systems and why DataHub excels [here](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained). Also read our -[LinkedIn Engineering blog post](https://engineering.linkedin.com/blog/2019/data-hub), check out our [Strata presentation](https://speakerdeck.com/shirshanka/the-evolution-of-metadata-linkedins-journey-strata-nyc-2019) and watch our [Crunch Conference Talk](https://www.youtube.com/watch?v=OB-O0Y6OYDE). You should also visit [DataHub Architecture](docs/architecture/architecture.md) to get a better understanding of how DataHub is implemented. +Modern data stacks are fragmented across dozens of tools. DataHub solves this by acting as a real-time metadata graph that continuously streams metadata from all your data sources, creating a single source of truth. -## Features & Roadmap +## Why DataHub? -Check out DataHub's [Features](docs/features.md) & [Roadmap](https://feature-requests.datahubproject.io/roadmap). +- **Built for Scale**: Proven at LinkedIn managing 100,000+ datasets, 10M+ daily queries +- **Real-Time Streaming**: Metadata updates in seconds, not hours or days +- **Universal Connectors**: [100+ integrations](https://docs.datahub.com/integrations) for warehouses, databases, BI, ML, orchestration +- **Developer-First**: Rich APIs (GraphQL, REST), Python SDK, CLI tools +- Enterprise Ready: Battle-tested security, authentication, authorization, and audit trails +- **Open Source**: [Apache 2.0 licensed](./LICENSE), vendor-neutral, community-driven -## Demo and Screenshots +## Core Features + + +
+ +| Features | Description | +|----------|-------------| +| 🔍 [**Data Discovery**](https://datahub.com/products/data-discovery/) | Effortlessly discover and get context on trustworthy data | +| 👁️ [**Data Observability**](https://datahub.com/products/data-observability) | Detect, resolve, and prevent data quality issues before they impact your business | +| 🏛️ [**Data Governance**](https://datahub.com/products/data-governance)| Ensure every data asset is accounted for by continuously fulfilling governance standards. | +| 📊 [**Impact Analysis**](https://docs.datahub.com/docs/act-on-metadata/impact-analysis) | Understand downstream impact before making changes | [Lineage Docs](https://docs.datahub.com/docs/lineage) | -There's a [hosted demo environment](https://demo.datahub.com/) courtesy of DataHub where you can explore DataHub without installing it locally. ## Quickstart Please follow the [DataHub Quickstart Guide](https://docs.datahub.com/docs/quickstart) to run DataHub locally using [Docker](https://docker.com). -## Development +``` +python3 -m pip install --upgrade acryl-datahub +datahub docker quickstart +``` + +What you get: +- ✅ DataHub GMS (backend metadata service) +- ✅ DataHub Frontend (React UI) +- ✅ Elasticsearch (search & analytics) +- ✅ MySQL (metadata storage) +- ✅ Kafka + Schema Registry (streaming) +- ✅ Sample data + + + > You can alwasy try our [hosted demo]((https://demo.datahub.com/)) - Explore DataHub with sample data, no installation needed! + + +## Trusted by Industry Leaders +DataHub powers data discovery and governance at some of the world's most data-driven organizations. + +[Here are the companies](https://datahub.com/resources/?2004611554=dh-stories) that have officially adopted DataHub. Please feel free to add yours to the list if we missed it. + + + +## Community + +Join our [Slack workspace](https://datahub.com/slack?utm_source=github&utm_medium=readme&utm_campaign=github_readme) for discussions and important announcements. You can also find out more about our upcoming [town hall meetings](docs/townhalls.md) and view past recordings. + + +## Contributing + +We welcome contributions from the community. Please refer to our [Contributing Guidelines](docs/CONTRIBUTING.md) for more details. We also have a [contrib](contrib) directory for incubating experimental features. If you're looking to build & modify datahub please take a look at our [Development Guide](https://docs.datahub.com/docs/developers). -
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