Sharc.Vector 1.2.80

.NET 10.0 This package targets .NET 10.0. The package is compatible with this framework or higher. 
dotnet add package Sharc.Vector --version 1.2.80
                    


                    

                
NuGet\Install-Package Sharc.Vector -Version 1.2.80
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="Sharc.Vector" Version="1.2.80" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
<PackageVersion Include="Sharc.Vector" Version="1.2.80" />
                    


                            Directory.Packages.props
                        

                    

                
<PackageReference Include="Sharc.Vector" />
                    


                            Project file
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package. 
paket add Sharc.Vector --version 1.2.80
                    


                    

                
#r "nuget: Sharc.Vector, 1.2.80"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
#:package Sharc.Vector@1.2.80
#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package. 
#addin nuget:?package=Sharc.Vector&version=1.2.80
                    


                            Install as a Cake Addin
                        

                    

                
#tool nuget:?package=Sharc.Vector&version=1.2.80
                    


                            Install as a Cake Tool

Sharc.Vector

SIMD-accelerated vector similarity search for Sharc.

Features

  • Zero-copy BLOB decode: MemoryMarshal.Cast<byte, float> directly on cached page buffers
  • SIMD distance: Cosine, Euclidean, and Dot Product via TensorPrimitives (AVX-512 when available)
  • Top-K nearest neighbor: Fixed-capacity heap selection
  • Metadata pre-filtering: Apply WHERE filters before distance computation
  • JitQuery integration: Reuses Sharc's pre-compiled query handles

Quick Start

using Sharc;
using Sharc.Vector;

using var db = SharcDatabase.Open("knowledge.db");

// Create a reusable vector search handle
using var vq = db.Vector("documents", "embedding", DistanceMetric.Cosine);

// Optional: metadata pre-filter (applied before distance computation)
vq.Where(FilterStar.Column("category").Eq("science"));

// Find the 10 nearest neighbors
float[] queryVector = GetEmbedding("How do quantum computers work?");
var results = vq.NearestTo(queryVector, k: 10);

foreach (var match in results.Matches)
    Console.WriteLine($"Row {match.RowId}: distance={match.Distance:F4}");

Store Vectors

Vectors are stored as BLOB columns in regular SQLite tables:

byte[] vectorBlob = BlobVectorCodec.Encode(embeddingModel.Encode("Hello world"));
// Store vectorBlob as a BLOB column value via SharcWriter

Performance

Operation Allocation Notes
Per-row distance 0 B Zero-copy BLOB → float reinterpret
10K vectors (384-dim) ~5-10 ms TensorPrimitives SIMD
100K vectors (384-dim) ~50-100 ms Linear scan baseline

Requirements

  • .NET 8.0+
  • System.Numerics.Tensors (included automatically)
Product Compatible and additional computed target framework versions.
.NET net10.0 is compatible.  net10.0-android was computed.  net10.0-browser was computed.  net10.0-ios was computed.  net10.0-maccatalyst was computed.  net10.0-macos was computed.  net10.0-tvos was computed.  net10.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last Updated
1.2.80 83 2/27/2026
1.2.77 95 2/26/2026
1.2.65 81 2/26/2026
1.2.59 85 2/25/2026
1.1.2-beta 78 2/24/2026