datahub/docs/what/gma.md

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# What is Generalized Metadata Architecture (GMA)?
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GMA is the backend infrastructure for DataHub. Unlike existing architectures, GMA leverages multiple storage technologies to efficiently service the four most commonly used query patterns
- Document-oriented CRUD
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- Complex queries (including joining distributed tables)
- Graph traversal
- Fulltext search and autocomplete
GMA also embraces a distributed model, where each team owns, develops and operates their own metadata services (known as [GMS](gms.md)), while the metadata are automatically aggregated to populate the central [metadata graph](graph.md) and [search indexes](search-index.md). This is made possible by standardizing the metadata models and the access layer.
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We strongly believe that GMA can bring tremendous leverage to any team that has a need to store and access metadata.
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Moreover, standardizing metadata modeling promotes a model-first approach to developments, resulting in a more concise, consistent, and highly connected metadata ecosystem that benefits all DataHub users.