EFCore.SqlServer.VectorSearch

Important

Starting EF 10, the SQL Server provider contains full, built-in support for vector search. This plugin is no longer needed for EF 10 and above, and will be deprecated.

For earlier versions of EF, note that this plugin is in prerelease status and not officially supported.

This Entity Framework Core plugin provides integration between older versions of EF and Vector Support in Azure SQL Database and SQL Server 2025, allowing LINQ to be used to perform vector similarity search, and seamless insertion/retrieval of vector data.

To use the plugin, reference the EFCore.SqlServer.VectorSearch nuget package, and enable the plugin by adding UseVectorSearch() to your UseSqlServer() or UseAzureSql() config as follows:

builder.Services.AddDbContext<ProductContext>(options =>
  options.UseSqlServer("<connection string>", o => o.UseVectorSearch()));

Once the plugin has been enabled, add an ordinary float[] property to the .NET type being mapped with EF:

public class Product
{
    public int Id { get; set; }
    public float[] Embedding { get; set; }
}

Finally, configure the property to be mapped as a vector by letting EF Core know using the HasColumnType method. Use the vector type and specify the number of dimension that your vector will have:

protected override void OnModelCreating(ModelBuilder modelBuilder)
{
    modelBuilder.Entity<Product>().Property(p => p.Embedding).HasColumnType("vector(3)");
}

That's it - you can now perform similarity search in LINQ queries! For example, to get the top 5 most similar products:

var someVector = new[] { 1f, 2f, 3f };
var products = await context.Products
    .OrderBy(p => EF.Functions.VectorDistance("cosine", p.Embedding, someVector))
    .Take(5)
    .ToArrayAsync();

A full sample using EF Core and vectors is available here:

Note

The VECTOR_SEARCH() function (in preview) for approximate search with DiskANN is not supported.

Azure SQL DB Vector Samples - EF-Core Sample

Ideas? Issues? Let us know on the issues page.