Migrating from Qdrant to Meilisearch

mkdir qdrant-meilisearch-migration
cd qdrant-meilisearch-migration
npm init -y
touch script.js

npm install -s @qdrant/js-client-rest meilisearch

const { QdrantClient } = require("@qdrant/js-client-rest");

const qdrantClient = new QdrantClient({
  url: "QDRANT_URL",
  // apiKey: "QDRANT_API_KEY", // if authentication is enabled
});

const COLLECTION_NAME = "YOUR_COLLECTION_NAME";
const BATCH_SIZE = 1000;

async function fetchAllPoints() {
  const records = [];
  let offset = null;

  while (true) {
    const response = await qdrantClient.scroll(COLLECTION_NAME, {
      limit: BATCH_SIZE,
      offset: offset,
      with_payload: true,
      with_vectors: true,
    });

    records.push(...response.points);

    if (!response.next_page_offset) break;
    offset = response.next_page_offset;
  }

  return records;
}

function prepareDocuments(points, keepVectors = false) {
  return points.map((point) => {
    // Extract payload fields as top-level document fields
    const doc = { ...point.payload };
    doc.id = String(point.id);

    // Option B: keep existing vectors
    if (keepVectors && point.vector) {
      if (typeof point.vector === "object" && !Array.isArray(point.vector)) {
        // Named vectors: { "text-embedding": [...], "image-embedding": [...] }
        doc._vectors = point.vector;
      } else {
        // Single unnamed vector
        doc._vectors = { default: point.vector };
      }
    }

    return doc;
  });
}

function convertGeoFields(doc, geoFieldName) {
  if (doc[geoFieldName]) {
    const geo = doc[geoFieldName];
    doc._geo = {
      lat: geo.lat,
      lng: geo.lon, // Qdrant uses "lon", Meilisearch uses "lng"
    };
    delete doc[geoFieldName];
  }
  return doc;
}

const { MeiliSearch } = require("meilisearch");

const meiliClient = new MeiliSearch({
  host: "MEILI_HOST",
  apiKey: "MEILI_API_KEY",
});
const meiliIndex = meiliClient.index("MEILI_INDEX_NAME");

const UPLOAD_BATCH_SIZE = 100000;
await meiliIndex.addDocumentsInBatches(documents, UPLOAD_BATCH_SIZE);

node script.js

const { QdrantClient } = require("@qdrant/js-client-rest");
const { MeiliSearch } = require("meilisearch");

const COLLECTION_NAME = "YOUR_COLLECTION_NAME";
const FETCH_BATCH_SIZE = 1000;
const UPLOAD_BATCH_SIZE = 100000;
const KEEP_VECTORS = false; // set to true to preserve existing vectors

(async () => {
  // Connect to Qdrant
  const qdrantClient = new QdrantClient({
    url: "QDRANT_URL",
  });

  // Fetch all points using Scroll API
  const records = [];
  let offset = null;

  while (true) {
    const response = await qdrantClient.scroll(COLLECTION_NAME, {
      limit: FETCH_BATCH_SIZE,
      offset: offset,
      with_payload: true,
      with_vectors: KEEP_VECTORS,
    });

    records.push(...response.points);

    if (!response.next_page_offset) break;
    offset = response.next_page_offset;
  }

  // Prepare documents for Meilisearch
  const documents = records.map((point) => {
    const doc = { ...point.payload };
    doc.id = String(point.id);

    if (KEEP_VECTORS && point.vector) {
      if (typeof point.vector === "object" && !Array.isArray(point.vector)) {
        doc._vectors = point.vector;
      } else {
        doc._vectors = { default: point.vector };
      }
    }

    return doc;
  });

  console.log(`Fetched ${documents.length} points from Qdrant`);

  // Upload to Meilisearch
  const meiliClient = new MeiliSearch({
    host: "MEILI_HOST",
    apiKey: "MEILI_API_KEY",
  });
  const meiliIndex = meiliClient.index("MEILI_INDEX_NAME");

  await meiliIndex.addDocumentsInBatches(documents, UPLOAD_BATCH_SIZE);
  console.log("Migration complete");
})();