Create Non Linear Algorithm Index

Schema

This request accepts an optional schema field. When it is omitted, the server uses the public schema. Set schema to target a store in another schema.

The CreateNonLinearAlgorithmIndex request creates a non-linear index (HNSW) to speed up similarity searches.

• Input: Store name and list of non-linear indices to create.

• Behavior: Builds the specified non-linear index structure for faster similarity queries.

• Response: Confirmation of index creation.

Create an HNSW Index

Click to expand source code

TypeScript

import { createDbClient } from "ahnlich-client-node";
import { CreateNonLinearAlgorithmIndex } from "ahnlich-client-node/grpc/db/query_pb";
import { NonLinearIndex, HNSWConfig } from "ahnlich-client-node/grpc/algorithm/nonlinear_pb";

async function createHNSWIndex() {
  const client = createDbClient("127.0.0.1:1369");

  await client.createNonLinearAlgorithmIndex(
    new CreateNonLinearAlgorithmIndex({
      store: "my_store",
      schema: "analytics",
      nonLinearIndices: [
        new NonLinearIndex({
          index: { case: "hnsw", value: new HNSWConfig() },
        }),
      ],
    })
  );

  console.log("HNSW index created successfully");
}

createHNSWIndex();

Parameters

Parameter	Type	Required	Description
store	string	Yes	The name of the store
nonLinearIndices	NonLinearIndex[]	Yes	List of indices to create

Index Types

Type	Description	Best For
HNSW	Hierarchical Navigable Small World	High dimensions, approximate but fast

Notes

• Non-linear indices dramatically improve GetSimN performance on large stores
• HNSW is generally recommended for high-dimensional embeddings (128+)
• Building indices takes time and memory proportional to store size
• You can have multiple index types on the same store