Elasticsearch vector store

The ElasticSearchVector class provides vector search using Elasticsearch with its dense_vector field type and k-NN search capabilities. It's part of the @mastra/elasticsearch package.

Installation

npm install @mastra/elasticsearch@latest

Usage

import { ElasticSearchVector } from "@mastra/elasticsearch";

const store = new ElasticSearchVector({
  id: "elasticsearch-vector",
  url: process.env.ELASTICSEARCH_URL,
});

// Create an index
await store.createIndex({
  indexName: "my-collection",
  dimension: 1536,
});

// Add vectors with metadata
const vectors = [[0.1, 0.2, ...], [0.3, 0.4, ...]];
const metadata = [
  { text: "first document", category: "A" },
  { text: "second document", category: "B" }
];
await store.upsert({
  indexName: "my-collection",
  vectors,
  metadata,
});

// Query similar vectors
const results = await store.query({
  indexName: "my-collection",
  queryVector: [0.1, 0.2, ...],
  topK: 10,
  filter: { category: "A" },
});

Constructor options

<PropertiesTable content={[ { name: 'id', type: 'string', description: 'Unique identifier for this vector store instance', }, { name: 'url', type: 'string', description: "Elasticsearch connection URL (e.g., 'http://localhost:9200')", }, ]} />

Methods

createIndex()

Creates a new index with the specified configuration.

<PropertiesTable content={[ { name: 'indexName', type: 'string', description: 'Name of the index to create', }, { name: 'dimension', type: 'number', description: 'Vector dimension (must match your embedding model)', }, { name: 'metric', type: "'cosine' | 'euclidean' | 'dotproduct'", isOptional: true, defaultValue: 'cosine', description: 'Distance metric for similarity search', }, ]} />

upsert()

Adds or updates vectors and their metadata in the index.

<PropertiesTable content={[ { name: 'indexName', type: 'string', description: 'Name of the index to insert into', }, { name: 'vectors', type: 'number[][]', description: 'Array of embedding vectors', }, { name: 'metadata', type: 'Record<string, any>[]', isOptional: true, description: 'Metadata for each vector', }, { name: 'ids', type: 'string[]', isOptional: true, description: 'Optional vector IDs (auto-generated if not provided)', }, ]} />

query()

Searches for similar vectors with optional metadata filtering.

<PropertiesTable content={[ { name: 'indexName', type: 'string', description: 'Name of the index to search in', }, { name: 'queryVector', type: 'number[]', description: 'Query vector to find similar vectors for', }, { name: 'topK', type: 'number', isOptional: true, defaultValue: '10', description: 'Number of results to return', }, { name: 'filter', type: 'Record<string, any>', isOptional: true, description: 'Metadata filters', }, { name: 'includeVector', type: 'boolean', isOptional: true, defaultValue: 'false', description: 'Whether to include vector data in results', }, ]} />

describeIndex()

Gets information about an index.

<PropertiesTable content={[ { name: 'indexName', type: 'string', description: 'Name of the index to describe', }, ]} />

Returns:

interface IndexStats {
  dimension: number
  count: number
  metric: 'cosine' | 'euclidean' | 'dotproduct'
}

deleteIndex()

Deletes an index and all its data.

<PropertiesTable content={[ { name: 'indexName', type: 'string', description: 'Name of the index to delete', }, ]} />

listIndexes()

Lists all vector indexes.

Returns: Promise<string[]>

updateVector()

Update a single vector by ID or by metadata filter. Either id or filter must be provided, but not both.

<PropertiesTable content={[ { name: 'indexName', type: 'string', description: 'Name of the index containing the vector', }, { name: 'id', type: 'string', isOptional: true, description: 'ID of the vector to update (mutually exclusive with filter)', }, { name: 'filter', type: 'Record<string, any>', isOptional: true, description: 'Metadata filter to identify vector(s) to update (mutually exclusive with id)', }, { name: 'update', type: 'object', description: 'Update data containing vector and/or metadata', }, { name: 'update.vector', type: 'number[]', isOptional: true, description: 'New vector data', }, { name: 'update.metadata', type: 'Record<string, any>', isOptional: true, description: 'New metadata', }, ]} />

deleteVector()

Deletes a single vector by its ID.

<PropertiesTable content={[ { name: 'indexName', type: 'string', description: 'Name of the index containing the vector', }, { name: 'id', type: 'string', description: 'ID of the vector to delete', }, ]} />

deleteVectors()

Delete multiple vectors by IDs or by metadata filter. Either ids or filter must be provided, but not both.

<PropertiesTable content={[ { name: 'indexName', type: 'string', description: 'Name of the index containing the vectors to delete', }, { name: 'ids', type: 'string[]', isOptional: true, description: 'Array of vector IDs to delete (mutually exclusive with filter)', }, { name: 'filter', type: 'Record<string, any>', isOptional: true, description: 'Metadata filter to identify vectors to delete (mutually exclusive with ids)', }, ]} />

Response types

Query results are returned in this format:

interface QueryResult {
  id: string
  score: number
  metadata: Record<string, any>
  vector?: number[] // Only included if includeVector is true
}

Related

• Metadata Filters