/azure-search-documents-dotnet

name: azure-search-documents-dotnet
description: Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search.
risk: unknown
source: community
date_added: '2026-02-27'

Azure.Search.Documents (.NET)

Build search applications with full-text, vector, semantic, and hybrid search capabilities.

Installation

dotnet add package Azure.Search.Documents
dotnet add package Azure.Identity

**Current Versions**: Stable v11.7.0, Preview v11.8.0-beta.1

Environment Variables

SEARCH_ENDPOINT=https://<search-service>.search.windows.net
SEARCH_INDEX_NAME=<index-name>
# For API key auth (not recommended for production)
SEARCH_API_KEY=<api-key>

Authentication

**DefaultAzureCredential (preferred)**:

using Azure.Identity;
using Azure.Search.Documents;

var credential = new DefaultAzureCredential();
var client = new SearchClient(
    new Uri(Environment.GetEnvironmentVariable("SEARCH_ENDPOINT")),
    Environment.GetEnvironmentVariable("SEARCH_INDEX_NAME"),
    credential);

**API Key**:

using Azure;
using Azure.Search.Documents;

var credential = new AzureKeyCredential(
    Environment.GetEnvironmentVariable("SEARCH_API_KEY"));
var client = new SearchClient(
    new Uri(Environment.GetEnvironmentVariable("SEARCH_ENDPOINT")),
    Environment.GetEnvironmentVariable("SEARCH_INDEX_NAME"),
    credential);

Client Selection

| Client | Purpose | |--------|---------| | `SearchClient` | Query indexes, upload/update/delete documents | | `SearchIndexClient` | Create/manage indexes, synonym maps | | `SearchIndexerClient` | Manage indexers, skillsets, data sources |

Index Creation

Using FieldBuilder (Recommended)

using Azure.Search.Documents.Indexes;
using Azure.Search.Documents.Indexes.Models;

// Define model with attributes
public class Hotel
{
    [SimpleField(IsKey = true, IsFilterable = true)]
    public string HotelId { get; set; }

    [SearchableField(IsSortable = true)]
    public string HotelName { get; set; }

    [SearchableField(AnalyzerName = LexicalAnalyzerName.EnLucene)]
    public string Description { get; set; }

    [SimpleField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
    public double? Rating { get; set; }

    [VectorSearchField(VectorSearchDimensions = 1536, VectorSearchProfileName = "vector-profile")]
    public ReadOnlyMemory<float>? DescriptionVector { get; set; }
}

// Create index
var indexClient = new SearchIndexClient(endpoint, credential);
var fieldBuilder = new FieldBuilder();
var fields = fieldBuilder.Build(typeof(Hotel));

var index = new SearchIndex("hotels")
{
    Fields = fields,
    VectorSearch = new VectorSearch
    {
        Profiles = { new VectorSearchProfile("vector-profile", "hnsw-algo") },
        Algorithms = { new HnswAlgorithmConfiguration("hnsw-algo") }
    }
};

await indexClient.CreateOrUpdateIndexAsync(index);

Manual Field Definition

var index = new SearchIndex("hotels")
{
    Fields =
    {
        new SimpleField("hotelId", SearchFieldDataType.String) { IsKey = true, IsFilterable = true },
        new SearchableField("hotelName") { IsSortable = true },
        new SearchableField("description") { AnalyzerName = LexicalAnalyzerName.EnLucene },
        new SimpleField("rating", SearchFieldDataType.Double) { IsFilterable = true, IsSortable = true },
        new SearchField("descriptionVector", SearchFieldDataType.Collection(SearchFieldDataType.Single))
        {
            VectorSearchDimensions = 1536,
            VectorSearchProfileName = "vector-profile"
        }
    }
};

Document Operations

var searchClient = new SearchClient(endpoint, indexName, credential);

// Upload (add new)
var hotels = new[] { new Hotel { HotelId = "1", HotelName = "Hotel A" } };
await searchClient.UploadDocumentsAsync(hotels);

// Merge (update existing)
await searchClient.MergeDocumentsAsync(hotels);

// Merge or Upload (upsert)
await searchClient.MergeOrUploadDocumentsAsync(hotels);

// Delete
await searchClient.DeleteDocumentsAsync("hotelId", new[] { "1", "2" });

// Batch operations
var batch = IndexDocumentsBatch.Create(
    IndexDocumentsAction.Upload(hotel1),
    IndexDocumentsAction.Merge(hotel2),
    IndexDocumentsAction.Delete(hotel3));
await searchClient.IndexDocumentsAsync(batch);

Search Patterns

Basic Search

var options = new SearchOptions
{
    Filter = "rating ge 4",
    OrderBy = { "rating desc" },
    Select = { "hotelId", "hotelName", "rating" },
    Size = 10,
    Skip = 0,
    IncludeTotalCount = true
};

SearchResults<Hotel> results = await searchClient.SearchAsync<Hotel>("luxury", options);

Console.WriteLine($"Total: {results.TotalCount}");
await foreach (SearchResult<Hotel> result in results.GetResultsAsync())
{
    Console.WriteLine($"{result.Document.HotelName} (Score: {result.Score})");
}

Faceted Search

var options = new SearchOptions
{
    Facets = { "rating,count:5", "category" }
};

var results = await searchClient.SearchAsync<Hotel>("*", options);

foreach (var facet in results.Value.Facets["rating"])
{
    Console.WriteLine($"Rating {facet.Value}: {facet.Count}");
}

Autocomplete and Suggestions

// Autocomplete
var autocompleteOptions = new AutocompleteOptions { Mode = AutocompleteMode.OneTermWithContext };
var autocomplete = await searchClient.AutocompleteAsync("lux", "suggester-name", autocompleteOptions);

// Suggestions
var suggestOptions = new SuggestOptions { UseFuzzyMatching = true };
var suggestions = await searchClient.SuggestAsync<Hotel>("lux", "suggester-name", suggestOptions);

Vector Search

See references/vector-search.md for detailed patterns.

using Azure.Search.Documents.Models;

// Pure vector search
var vectorQuery = new VectorizedQuery(embedding)
{
    KNearestNeighborsCount = 5,
    Fields = { "descriptionVector" }
};

v