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61 lines
4.3 KiB
Markdown
61 lines
4.3 KiB
Markdown
---
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title: "Components"
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---
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# DataHub Components Overview
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The DataHub platform consists of the components shown in the following diagram.
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## Metadata Store
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The Metadata Store is responsible for storing the [Entities & Aspects](https://datahubproject.io/docs/metadata-modeling/metadata-model/) comprising the Metadata Graph. This includes
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exposing an API for [ingesting metadata](https://datahubproject.io/docs/metadata-service#ingesting-entities), [fetching Metadata by primary key](https://datahubproject.io/docs/metadata-service#retrieving-entities), [searching entities](https://datahubproject.io/docs/metadata-service#search-an-entity), and [fetching Relationships](https://datahubproject.io/docs/metadata-service#get-relationships-edges) between
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entities. It consists of a Spring Java Service hosting a set of [Rest.li](https://linkedin.github.io/rest.li/) API endpoints, along with
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MySQL, Elasticsearch, & Kafka for primary storage & indexing.
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Get started with the Metadata Store by following the [Quickstart Guide](https://datahubproject.io/docs/quickstart/).
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## Metadata Models
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Metadata Models are schemas defining the shape of the Entities & Aspects comprising the Metadata Graph, along with the relationships between them. They are defined
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using [PDL](https://linkedin.github.io/rest.li/pdl_schema), a modeling language quite similar in form to Protobuf while serializes to JSON. Entities represent a specific class of Metadata
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Asset such as a Dataset, a Dashboard, a Data Pipeline, and beyond. Each *instance* of an Entity is identified by a unique identifier called an `urn`. Aspects represent related bundles of data attached
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to an instance of an Entity such as its descriptions, tags, and more. View the current set of Entities supported [here](https://datahubproject.io/docs/metadata-modeling/metadata-model#exploring-datahubs-metadata-model).
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Learn more about DataHub models Metadata [here](https://datahubproject.io/docs/metadata-modeling/metadata-model/).
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## Ingestion Framework
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The Ingestion Framework is a modular, extensible Python library for extracting Metadata from external source systems (e.g.
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Snowflake, Looker, MySQL, Kafka), transforming it into DataHub's [Metadata Model](https://datahubproject.io/docs/metadata-modeling/metadata-model/), and writing it into DataHub via
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either Kafka or using the Metadata Store Rest APIs directly. DataHub supports an [extensive list of Source connectors](https://datahubproject.io/docs/metadata-ingestion/#installing-plugins) to choose from, along with
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a host of capabilities including schema extraction, table & column profiling, usage information extraction, and more.
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Getting started with the Ingestion Framework is as simple: just define a YAML file and execute the `datahub ingest` command.
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Learn more by heading over the the [Metadata Ingestion](https://datahubproject.io/docs/metadata-ingestion/) guide.
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## GraphQL API
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The [GraphQL](https://graphql.org/) API provides a strongly-typed, entity-oriented API that makes interacting with the Entities comprising the Metadata
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Graph simple, including APIs for adding and removing tags, owners, links & more to Metadata Entities! Most notably, this API is consumed by the User Interface (discussed below) for enabling Search & Discovery, Governance, Observability
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and more.
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To get started using the GraphQL API, check out the [Getting Started with GraphQL](https://datahubproject.io/docs/api/graphql/getting-started) guide.
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## User Interface
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DataHub comes with a React UI including an ever-evolving set of features to make Discovering, Governing, & Debugging your Data Assets easy & delightful.
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For a full overview of the capabilities currently supported, take a look at the [Features](https://datahubproject.io/docs/features/) overview. For a look at what's coming next,
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head over to the [Roadmap](https://datahubproject.io/docs/roadmap/).
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## Learn More
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Learn more about the specifics of the [DataHub Architecture](./architecture/architecture.md) in the Architecture Overview. Learn about using & developing the components
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of the Platform by visiting the Module READMEs.
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## Feedback / Questions / Concerns
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We want to hear from you! For any inquiries, including Feedback, Questions, or Concerns, reach out on [Slack](https://datahubspace.slack.com/join/shared_invite/zt-nx7i0dj7-I3IJYC551vpnvvjIaNRRGw#/shared-invite/email)!
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