Node.js Analytics SDK Quickstart Guide

Install, connect, try. A quick start guide to get you up and running with Enterprise Analytics and the Node.js Analytics SDK.

Enterprise Analytics is a real-time analytical database (RT-OLAP) for real time apps and operational intelligence. Although maintaining some syntactic similarities with the operational SDKs, the Node.js Analytics SDK is developed from the ground-up for column-based analytical use cases, and supports streaming APIs to handle large datasets.

Before You Start

Install and configure an Enterprise Analytics Cluster.

Prerequisites

The Analytics Node.js SDK supports LTS versions of Node.js — these are 24 and 22 at the time of the 1.0.0 release (August 2025). See the compatibility page for more information about platform support.

Getting the SDK

The SDK can be installed via npm:

npm install couchbase-analytics

For other installation methods, see the installation page.

Connecting and Executing a Query

To use these examples, create a collection to work upon by importing the travel-sample dataset into your cluster.

CommonJS

const analytics = require('couchbase-analytics')

async function main() {
    // Update this to your cluster
    const clusterConnStr = 'https://<your_hostname>:<PORT>'
    const username = 'username'
    const password = 'Password123!'
    // User Input ends here.

    const credential = new analytics.Credential(username, password)
    const cluster = analytics.createInstance(clusterConnStr, credential)

    // Execute a streaming query with positional arguments.
    let qs = 'SELECT * FROM `travel-sample`.inventory.airline LIMIT 10;'
    let res = await cluster.executeQuery(qs)
    for await (let row of res.rows()) {
        console.log('Found row: ', row)
    }
    console.log('Metadata: ', res.metadata())

    // Execute a streaming query with positional arguments.
    qs =
        'SELECT * FROM `travel-sample`.inventory.airline WHERE country=$1 LIMIT $2;'
    res = await cluster.executeQuery(qs, { parameters: ['United States', 10] })
    for await (let row of res.rows()) {
        console.log('Found row: ', row)
    }
    console.log('Metadata: ', res.metadata())

    // Execute a streaming query with named parameters.
    qs =
        'SELECT * FROM `travel-sample`.inventory.airline WHERE country=$country LIMIT $limit;'
    res = await cluster.executeQuery(qs, {
        parameters: { country: 'United States', limit: 10 },
    })
    for await (let row of res.rows()) {
        console.log('Found row: ', row)
    }
    console.log('Metadata: ', res.metadata())
}

main()
    .then(() => {
        console.log('Finished.  Exiting app...')
    })
    .catch((err) => {
        console.log('ERR: ', err)
        console.log('Exiting app...')
        process.exit(1)
    })

ES Modules

import { Credential, createInstance } from "couchbase-analytics"

async function main() {
    // Update this to your cluster
    const clusterConnStr = 'https://<your_hostname>:<PORT>'
    const username = 'username'
    const password = 'Password123!'
    // User Input ends here.

    const credential = new Credential(username, password)
    const cluster = createInstance(clusterConnStr, credential)

    // Execute a streaming query with positional arguments.
    let qs = "SELECT * FROM `travel-sample`.inventory.airline LIMIT 10;"
    let res = await cluster.executeQuery(qs)
    for await (let row of res.rows()) {
        console.log("Found row: ", row)
    }
    console.log("Metadata: ", res.metadata())

    // Execute a streaming query with positional arguments.
    qs =
        "SELECT * FROM `travel-sample`.inventory.airline WHERE country=$1 LIMIT $2;"
    res = await cluster.executeQuery(qs, { parameters: ["United States", 10] })
    for await (let row of res.rows()) {
        console.log("Found row: ", row)
    }
    console.log("Metadata: ", res.metadata())

    // Execute a streaming query with named parameters.
    qs =
        "SELECT * FROM `travel-sample`.inventory.airline WHERE country=$country LIMIT $limit;"
    res = await cluster.executeQuery(qs, {
        parameters: { country: "United States", limit: 10 },
    })
    for await (let row of res.rows()) {
        console.log("Found row: ", row)
    }
    console.log("Metadata: ", res.metadata())
}

main()
    .then(() => {
        console.log("Finished.  Exiting app...")
    })
    .catch((err) => {
        console.log("ERR: ", err)
        console.log("Exiting app...")
        process.exit(1)
    })

Connection String

The clusterConnStr in the above example should takes the form of "https://<your_hostname>:" + PORT. The default port is 443, for TLS connections. You do not need to give a port number if you are using port 443 — hostname = "https://<your_hostname>" is effectively the same as `hostname = "https://<your_hostname>:" + "443"

If you are using a different port — for example, connecting to a cluster without a load balancer, directly to the Analytics port, 18095 — or not using TLS, then see the Connecting to Enterprise Analytics page.

Migration from Row-Based Analytics

If you are migrating a project from CBAS — our Analytics service on Capella Operational and Couchbase Server, using our operational SDKs — then information on migration can be found in the Enterprise Analytics docs.

In particular, refer to the SDK section of the Enterprise Analytics migration pages.