## Built with ❤️ by <img src="https://datahubproject.io/img/acryl-logo-light-mark.png" width="25"/> [Acryl Data](https://acryldata.io) and <img src="https://datahubproject.io/img/LI-In-Bug.png" width="25"/> [LinkedIn](https://engineering.linkedin.com)
> - Bringing The Power Of The DataHub Real-Time Metadata Graph To Everyone At Acryl Data: [Data Engineering Podcast](https://www.dataengineeringpodcast.com/acryl-data-datahub-metadata-graph-episode-230/)
> - Latest blog post [DataHub: Popular Metadata Architectures Explained](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained) @ LinkedIn Engineering Blog.
DataHub is an open-source metadata platform 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 and [DataHub Onboarding Guide](docs/modeling/extending-the-metadata-model.md) to understand how to extend DataHub for your own use cases.
Please follow the [DataHub Quickstart Guide](https://datahubproject.io/docs/quickstart) to get a copy of DataHub up & running locally using [Docker](https://docker.com). As the guide assumes some basic knowledge of Docker, we'd recommend you to go through the "Hello World" example of [A Docker Tutorial for Beginners](https://docker-curriculum.com) if Docker is completely foreign to you.
- [linkedin/datahub](https://github.com/linkedin/datahub): This repository contains the complete source code for DataHub's metadata model, metadata services, integration connectors and the web application.
See [Releases](https://github.com/linkedin/datahub/releases) page for more details. We follow the [SemVer Specification](https://semver.org) when versioning the releases and adopt the [Keep a Changelog convention](https://keepachangelog.com/) for the changelog format.
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.
Join our [slack workspace](https://slack.datahubproject.io) for discussions and important announcements. You can also find out more about our upcoming [town hall meetings](docs/townhalls.md) and view past recordings.
- [Saxo Bank: Enabling Data Discovery in Data Mesh](https://medium.com/datahub-project/enabling-data-discovery-in-a-data-mesh-the-saxo-journey-451b06969c8f)
- Bringing The Power Of The DataHub Real-Time Metadata Graph To Everyone At Acryl Data: [Data Engineering Podcast](https://www.dataengineeringpodcast.com/acryl-data-datahub-metadata-graph-episode-230/)