Update gma.md

mars-lan · web-flow · commit 7789ff9a7dda · 2020-01-15T23:02:39.000-08:00
diff --git a/docs/what/gma.md b/docs/what/gma.md
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 # What is Generalized Metadata Architecture (GMA)?
 
-GMA is the name for DataHub's backend infrastructure. Unlike any existing architectures, GMA will be able to efficiently service the three most common query patterns (`document-oriented`, `complex` & `graph` queries, and `fulltext search`) 
-&mdash; with minimal onboarding efforts needed. 
+GMA is the backend infrastrcuture for DataHub. Unlike existing architectures, GMA leverages multiple storage technologies to efficiently service the four most commonly used query patterns
+- Document-oriented CRUD 
+- 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. 
 
-GMA also embraces a distributed model, where each team owns, develops and operates their own [metadata services](gms.md), while the metadata are automatically aggregated to populate the central metadata graph and search indexes. 
-This is made possible by standardizing the metadata models and the access layer. 
 We strongly believe that GMA can bring tremendous leverage to any team that has a need to store and access metadata. 
-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.
+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.
