How to Use Vector Databases from Go (Pinecone, Weaviate, Milvus)

Web Database
2026-04-17T14:12:14+00:00
Connect to Pinecone, Weaviate, or Milvus in Go using their official client libraries to store and query vector embeddings for similarity search.

Use the official Go client libraries for Pinecone, Weaviate, or Milvus to connect, index vectors, and query them. For Weaviate, initialize the client with your endpoint and API key, then use the Batch object to add documents and the Query object to search by vector similarity.

package main

import (
	"context"
	"log"

	"github.com/weaviate/weaviate-go-client/v4/weaviate"
	"github.com/weaviate/weaviate-go-client/v4/weaviate/filters"
	"github.com/weaviate/weaviate-go-client/v4/weaviate/graphql"
)

func main() {
	ctx := context.Background()
	client, err := weaviate.New(weaviate.Config{
		Scheme: "http",
		Host:   "localhost:8080",
	})
	if err != nil {
		log.Fatal(err)
	}

	// Add a document
	err = client.Batch().ObjectBatcher().WithObject(
		&weaviate.Object{
			Class: "Document",
			Properties: map[string]any{
				"content": "Go is a programming language.",
			},
		},
	).Do(ctx)
	if err != nil {
		log.Fatal(err)
	}

	// Query by vector similarity
	res, err := client.GraphQL().Get().WithClassName("Document").
		WithNearVector(&graphql.NearVector{
			Vector: []float32{0.1, 0.2, 0.3},
			Certainty: 0.7,
		}).
		WithFields("content").
		Do(ctx)
	if err != nil {
		log.Fatal(err)
	}
	log.Printf("Results: %v", res)
}