Merge pull request #5553 from haileytap/vectors

[Azure Search] Unify vector content

Author: JamesJBarnett

articles/search/search-what-is-an-index.md

@@ -11,20 +11,21 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 05/19/2025
+ms.date: 06/20/2025
 ---
 
 # Search indexes in Azure AI Search
 
-In Azure AI Search, a *search index* is your searchable content, available to the search engine for indexing, full text search, vector search, hybrid search, and filtered queries. An index is defined by a schema and saved to the search service, with data import following as a second step. This content exists within your search service, apart from your primary data stores, which is necessary for the millisecond response times expected in modern search applications. Except for indexer-driven indexing scenarios, the search service never connects to or queries your source data.
+In Azure AI Search, a *search index* is your searchable content, available to the search engine for indexing, full-text search, vector search, hybrid search, and filtered queries. An index is defined by a schema and saved to the search service, with data import following as a second step. This content exists within your search service, apart from your primary data stores, which is necessary for the millisecond response times expected in modern search applications. Except for indexer-driven indexing scenarios, the search service never connects to or queries your source data.
 
-If you want to create and manage a search index, this article helps you understand the following points:
+This article covers the key concepts for creating and managing a search index, including:
 
 + Content (documents and schema)
 + Physical data structure
 + Basic operations
 
-Prefer to be hands-on right away? See [Create a search index](search-how-to-create-search-index.md) instead.
+> [!TIP]
+> Want to get started right away? See [Create a search index](search-how-to-create-search-index.md).
 
 ## Schema of a search index
 
@@ -111,21 +112,21 @@ Although you can add new fields at any time, existing field definitions are lock
 
 ## Physical structure and size
 
-In Azure AI Search, the physical structure of an index is largely an internal implementation. You can access its schema, query its content, monitor its size, and manage capacity, but the clusters themselves (inverted indexes, vector indexes, [shards](index-similarity-and-scoring.md#sharding-effects-on-query-results), and other files and folders) are managed internally by Microsoft.
+In Azure AI Search, the physical structure of an index is largely an internal implementation. You can access its schema, load and query its content, monitor its size, and manage its capacity. However, Microsoft manages the infrastructure and physical data structures stored with your search service.
 
-You can monitor index size in the **Search management > Indexes** page in the Azure portal, or by issuing a [GET INDEX request](/rest/api/searchservice/indexes/get) against your search service. You can also issue a [Service Statistics request](/rest/api/searchservice/get-service-statistics/get-service-statistics) and check the value of storage size.
+You can monitor index size on the **Search management > Indexes** page in the Azure portal. Alternatively, you can issue a [GET INDEX request](/rest/api/searchservice/indexes/get) against your search service or a [Service Statistics request](/rest/api/searchservice/get-service-statistics/get-service-statistics) to check the value of storage size.
 
-The size of an index is determined by:
+The size of an index is determined by the:
 
-+ Quantity and composition of your documents
-+ Attributes on individual fields
-+ Index configuration (specifically, whether you include suggesters)
++ Quantity and composition of your documents.
++ Attributes on individual fields.
++ Index configuration. Specifically, whether you include suggesters.
 
-Document composition and quantity are determined by what you choose to import. Remember that a search index should only contain searchable content. If source data includes binary fields, omit those fields unless you're using AI enrichment to crack and analyze the content to create text searchable information.
+Document composition and quantity are determined by what you choose to import. Remember that a search index should only contain searchable content. If source data includes binary fields, omit those fields unless you're using AI enrichment to crack and analyze the content to create text-searchable information.
 
-Field attributes determine behaviors. To support those behaviors, the indexing process creates the necessary data structures. For example, for a field of type `Edm.String`, "searchable" invokes [full text search](search-lucene-query-architecture.md), which scans inverted indexes for the tokenized term. In contrast, a "filterable" or "sortable" attribute supports iteration over unmodified strings. The example in the next section shows variations in index size based on the selected attributes.
+Field attributes determine behaviors. To support those behaviors, the indexing process creates the necessary data structures. For example, for a field of type `Edm.String`, "searchable" invokes [full-text search](search-lucene-query-architecture.md), which scans inverted indexes for the tokenized term. In contrast, a "filterable" or "sortable" attribute supports iteration over unmodified strings. The example in the next section shows variations in index size based on the selected attributes.
 
-[**Suggesters**](index-add-suggesters.md) are constructs that support type-ahead or autocomplete queries. As such, when you include a suggester, the indexing process creates the data structures necessary for verbatim character matches. Suggesters are implemented at the field level, so choose only those fields that are reasonable for type-ahead.
+[**Suggesters**](index-add-suggesters.md) are constructs that support type-ahead or autocomplete queries. When you include a suggester, the indexing process creates the data structures necessary for verbatim character matches. Suggesters are implemented at the field level, so choose only those fields that are reasonable for type-ahead.
 
 ### Example demonstrating the storage implications of attributes and suggesters
 
@@ -143,33 +144,33 @@ Also not reflected in the previous table is the effect of [analyzers](search-ana
 
 ## Basic operations and interaction
 
-Now that you have a better idea of what an index is, this section introduces index run time operations, including connecting to and securing a single index.
+Now that you have a better idea of what an index is, this section introduces index runtime operations, including connecting to and securing a single index.
 
 > [!NOTE]
-> When managing an index, be aware that there is no portal or API support for moving or copying an index. Instead, customers typically point their application deployment solution at a different search service (if using the same index name), or revise the name to create a copy on the current search service, and then build it.
+> There's no portal or API support for moving or copying an index. Typically, you either point your application deployment to a different search service (using the same index name) or revise the name to create a copy on your current search service and then build it.
 
 ### Index isolation
 
-In Azure AI Search, you work with one index at a time, where all index-related operations target a single index. There's no concept of related indexes or the joining of independent indexes for either indexing or querying. 
+In Azure AI Search, you work with one index at a time. All index-related operations target a single index. There's no concept of related indexes or the joining of independent indexes for either indexing or querying.
 
 ### Continuously available
 
-An index is immediately available for queries as soon as the first document is indexed, but won't be fully operational until all documents are indexed. Internally, a search index is [distributed across partitions and executes on replicas](search-capacity-planning.md#concepts-search-units-replicas-partitions). The physical index is managed internally. The logical index is managed by you.
+An index is immediately available for queries as soon as the first document is indexed, but it's not fully operational until all documents are indexed. Internally, an index is [distributed across partitions and executes on replicas](search-capacity-planning.md#concepts-search-units-replicas-partitions). The physical index is managed internally. You manage the logical index.
 
-An index is continuously available, with no ability to pause or take it offline. Because it's designed for continuous operation, any updates to its content, or additions to the index itself, happen in real time. As a result, queries might temporarily return incomplete results if a request coincides with a document update.
+An index is continuously available and can't be paused or taken offline. Because it's designed for continuous operation, updates to its content and additions to the index itself happen in real time. If a request coincides with a document update, queries might temporarily return incomplete results.
 
-Notice that query continuity exists for document operations (refreshing or deleting) and for modifications that don't affect the existing structure and integrity of the current index (such as adding new fields). If you need to make structural updates (changing existing fields), those are typically managed using a drop-and-rebuild workflow in a development environment, or by creating a new version of the index on production service.
+Query continuity exists for document operations, such as refreshing or deleting, and for modifications that don't affect the existing structure or integrity of an index, such as adding new fields. Structural updates, such as changing existing fields, are typically managed using a drop-and-rebuild workflow in a development environment or by creating a new version of the index on the production service.
 
-To avoid an [index rebuild](search-howto-reindex.md), some customers who are making small changes choose to "version" a field by creating a new one that coexists alongside a previous version. Over time, this leads to orphaned content in the form of obsolete fields or obsolete custom analyzer definitions, especially in a production index that is expensive to replicate. You can address these issues on planned updates to the index as part of index lifecycle management.
+To avoid an [index rebuild](search-howto-reindex.md), some customers who are making small changes "version" a field by creating a new one that coexists with a previous version. Over time, this leads to orphaned content by way of obsolete fields and obsolete custom analyzer definitions, especially in a production index that's expensive to replicate. You can address these issues during planned updates to the index as part of index lifecycle management.
 
 ### Endpoint connection and security
 
 All indexing and query requests target an index. Endpoints are usually one of the following:
 
 | Endpoint | Connection and access control |
 |----------|-------------------------------|
-| `<your-service>.search.windows.net/indexes` | Targets the indexes collection. Used when creating, listing, or deleting an index. Admin rights are required for these operations, available through admin [API keys](search-security-api-keys.md) or a [Search Contributor role](search-security-rbac.md#built-in-roles-used-in-search). |
-| `<your-service>.search.windows.net/indexes/<your-index>/docs` | Targets the documents collection of a single index. Used when querying an index or data refresh. For queries, read rights are sufficient, and available through query API keys or a data reader role. For data refresh, admin rights are required. |
+| `<your-service>.search.windows.net/indexes` | Targets the indexes collection. Used when creating, listing, or deleting an index. Admin rights are required for these operations and available through admin [API keys](search-security-api-keys.md) or a [Search Contributor role](search-security-rbac.md#built-in-roles-used-in-search). |
+| `<your-service>.search.windows.net/indexes/<your-index>/docs` | Targets the documents collection of a single index. Used when querying an index or data refresh. For queries, read rights are sufficient and available through query API keys or a data reader role. For data refresh, admin rights are required. |
 
 #### How to connect to Azure AI Search
 

articles/search/toc.yml

@@ -154,7 +154,7 @@ items:
     items:
     - name: Search index
       href: search-what-is-an-index.md
-    - name: Vector store
+    - name: Vector index
       href: vector-store.md
     - name: Knowledge store
       href: knowledge-store-concept-intro.md