The Simplest ElasticSearch Node.js Client

  • esta

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The Simplest ElasticSearch Node.js Module


Q: There is already an "official" ElasticSearch module, why create a new one...?
A: Have you tried using the official client...? Did you enjoy the experience?
We needed an easy way to create, read, update and search our ElasticSearch records from node.js. All the available modules were way too complicated to use for beginners. So we decided to invest the time to create something much simpler!
Creating a record in ElasticSearch from your node.js app using esta is
this simple:
var es = require('esta'); // the simplest way to use ElasticSearch in node.js!
es.create({'message':'ElasticSearch is awesome!'}, function(response){
  console.log('record created '+ response.created); // record created true

As you are about to
discover, there is a much easier way to use ElasticSearch!

Guide to esta Documentation

CREATE (Save) a (new) record
READ a record UPDATE an (existing) record DELETE a record
Philosophy / Background / Detail: Dev Dependencies



Install from NPM

npm install esta --save

CONNECT to ElasticSearch Cluster using ES.CONNECT(calback(response))

If you need to check the connection status to the ElasticSearch Instance/Cluster we expose the handy ES.CONNECT method:
var ES = require('esta');

ES.CONNECT(index, function (response) {
  // for more detailed stats see: STATS method below
Pass in the index name as the first argument if you have not set an ESINDEX environment variable.
example ES.CONNECT
{ status: 200,
  name: 'Ultragirl',
  cluster_name: 'elasticsearch',
   { number: '1.4.2',
     build_hash: '927caff6f05403e936c20bf4529f144f0c89fd8c',
     build_timestamp: '2014-12-16T14:11:12Z',
     build_snapshot: false,
     lucene_version: '4.10.2' },
  tagline: 'You Know, for Search' }

CRUD Methods

CREATE (Save) a (new) record using ES.CREATE(record, callback(response))

Creating a new record is easy:
// define the record you want to store:
var record = {
  date: new Date().toISOString(),
  message: 'Your amazing message goes here'
ES.CREATE(record, function(response) {
 // do what ever you like with the response
A typical successful ES.CREATE response:
{ _index: 'index',
  _type: 'type',
  _id: '112669114721',
  _version: 1,
  created: true }
Optional Fields for a New Record:
  • index can be compared to a Database in SQL
  • type is like the table in SQL-world or a collection in other NoSQL systems.
  • id is the unique key for your record. equivalent to the primary-key in a SQL-world

While its optional to set these on your record before asking esta to create it, we highly recommend using index, type and id to organise your records.

READ a record using ES.READ(record, callback(response))

READing your record:
// define the record you want to retrieve:
var record = {
  index: 'twitter',
  type: 'tweet',
  id: 1234, // or what ever GUID you want to lookup
ES.READ(record, function(response) {
 // do what ever you like with the response
A typical successful ES.READ response:
{ _index: 'twitter',
  _type: 'tweet',
  _id: '735981868114',
  _version: 1,
  found: true,
  _source: { message: 'My Awesome Message' }
Here source is the original data you inserted as the record.
Record NOT Found
When a record does not exist response.found is false. e.g:
{ _index: 'twitter',
  _type: 'tweet',
  _id: '804164689732',
  found: false }
Required Fields for a READing a Record

UPDATE an (existing) record using ES.UPDATE(record, callback(response))

UPDATE an existing record:
// define the record you want to store:
var record = {
  index: 'twitter',
  type: 'tweet',
  id: 1234, // or what ever GUID you want
  message: 'Revised message'
ES.UPDATE(record, function(response) {
 // do what ever you like with the response
A typical successful ES.UPDATE response:
{ _index: 'twitter',
  _type: 'tweet',
  _id: '639403095701',
  _version: 2,
  created: false }
Notice how the
gets incremented to 2
Required Fields for a Updating an Existing Record:
  • index we need to know which "database" our record is in
  • type "table"
  • id the unique key for the record you are updating.

Note: UPDATE actually performs an UPSERT
UPdate record if already exists or inSERT (create) if its new.

DELETE a record using ES.DELETE(record, callback(response))

// define the record you want to store:
var record = {
  type: 'tweet',
  index: 'twitter',
  id: 1234, // or what ever GUID you want
  message: 'Revised message'
ES.DELETE(record, function(response) {
 // do what ever you like with the response
A typical successful ES.DELETE response:
{ found: true,
  _index: 'twitter',
  _type: 'tweet',
  _id: '137167415115',
  _version: 2,
  deleted: true }
Notice how the deleted is true
Required Fields for a Deleting an Existing Record:

Obviously if the record is NOT Found, there is nothing to delete. In that case, the response look like this: (found is false)
{ found: false,
  _index: 'twitter',
  _type: 'tweet',
  _id: '951078315032',
  _version: 1 }
Versioning Records
ElasticSearch does not store revisions of your documents by default, we made a "BACKUP" method which stores previous versions of records, when ever they are updated or deleted.
The old versions are stored as different type to avoid polluting the main "table" with copies this type is named: {typename}_bak
For example, if a document has an id abc and its current version is 2 we can find the previous version (v1) of the document by issuing the following read query:
var backup = { index: 'twitter', type: 'tweets_bak', id: 'abc_1'}

SEARCH for Record(s) using ES.SEARCH(query, callback(response))

Searching is super easy:
// setup query:
var query = {
  index: 'twitter',
  type:  'tweet',
  field: 'text',     // the field we want to search in
  text:  'amazing'   // string we are searching for

SEARCH(query, function(response) {
  // console.log(res);
  t.equal( > 0, true,"✓ Search results found: "+;
A typical
successful ES.SEARCH response:
{ took: 8,
  timed_out: false,
  _shards: { total: 5, successful: 5, failed: 0 },
   { total: 924,
     max_score: 0.6355637,
      [ [Object],
The is 924 (the number of records that matched our SEARCH query)
Required Fields for a SEARCHing:
  • index we need to know which "database" our record is in
  • type "table"
  • field the field in the record you want to search in.
  • text the text you are searching for.

When NO RECORDS are FOUND the response will look this:
{ took: 2,
  timed_out: false,
  _shards: { total: 5, successful: 5, failed: 0 },
  hits: { total: 0, max_score: null, hits: [] } }
We check for if( > 0) { /* use/display results */ } else { /* show sad face */}
Here's the image we use:
no results

Get Cluster STATS using ES.STATS(callback(response))

The ES.STATS method exposes the ElasticSearch Instance/Cluster _stats see:
STATS(function (response) {
  // do something awesome response
ElasticSearch returns
rich information on cluster health, document count etc. see: #31
for complete STATS output

"Just Works" (Defaults to 12 Factor App

To help you get started as fast as possible, esta defaults to using your local machine for ElasticSearch.

Local/Dev Machine Beginner Friendly

Provided you already have ElasticSearch
installed (we recommend using Vagrant, see below), there is nothing to setup or configure to use esta on your local machine!

Heroku Heroku Compatible

If you are deploying your App to Heroku there are two ElasticSearch-as-a-Service providers that offer Free entry level service:
  • Bonsai:
  • SearchBox:

esta supports both of these providers out-of-the-box! as soon as you add the "addon" to your heroku app it "just works!"
Our Travis Build Process includes checks for both Bonsai and SearchBox: See:

(Travis) CI

Speaking of Travis-CI, if you are using their fine build tool, here's a sample .travis.yml file:
language: node_js
  - 0.12
  - elasticsearch
if you are
new to Travis-CI see:

(Optional) Use Vagrant to Run ElasticSearch vagrant up

If, like me you prefer not to have Java running on your dev machine (because its
chronically insecure
) I highly recommend using Vagrant to run a light-weight virtual machine to isolate ElasticSearch and only install Java in the VM.
The other obvious benefit of using Vagrant is that all your fellow developers will have exactly the same (latest) build so there's no risk of version incompatibility. Learn more at:
I've included a Vagrantfile in this repo which will get you up-and-running with Ubuntu, Node.js & ElasticSearch with a single command: vagrant up
all you need to do is run the following commands in your terminal:
vagrant up
vagrant ssh
sudo service elasticsearch start

If you have any questions, just ask!

Philosophy / Background / Detail

Why Create a New Library?

We wanted something
simpler and thus much easier to extend if you need to!
esta is easy to understand. The entire module is 129 lines of clear/clean/commented/DRY code; you can read & understand it all before breakfast!
Dive in at /lib. Each method has a corresponding file in /test

Practical Feature: Recover Accidentally Deleted Data

We wanted a way of "
" records (i.e. avoiding data loss.) If you like the idea of being able to recover accidentally deleted data, you will love our DELETE method see: lib/delete.js

Only Core Modules Dependency Status

Zero external dependencies (3rd party modules).
There are quite a few modules in the node ecosystem
for use with ElasticSearch. However, when I saw how many dependencies the "Official" ElasticSearch Node.js Module had and especially the number of DevDependencies, it made it hard to contribute to the project...
Our aim is to build something that only uses core modules with Stable APIs, so we never have to think about upgrading - it also makes it a lot easier for others to learn how the module works, which invites contribution from the community.
Given that ElasticSearch has a REST API we are only using Node's http (core) module. and this is kept DRY (only in one file) see: lib/httprequest.js

Dev Dependencies devDependency Status

We carefully select and only use well-maintained "pure" JavaScript modules in our development toolchain:
  • Tape for testing:
  • Istanbul for Code Coverage:
  • Chalk for colors in test output (readability)
  • Pre-commit for ensuring all commits pass strict quality checks before being pushed to GitHub. see:
  • jshint checks code style is consistent:
  • CodeClimate for tracking code quality and test coverage:

Code Quality Build Status Test Coverage Code Climate bitHound Score

If you are looking for a module you can trust, these are the "badges" you are looking for.

Contributing contributions welcome

All contributions are welcome.
If anything is unclear please create an issue:

Error Handling

Warning: Contains Opinion (based on experience)

Most of the Node.js developers I've worked with, don't handle errors well.
A typical (
bad) example:
if(error) {
  console.log(error); // this is worse than useless!
So instead of having of having code full of if(err) ... we have
deliberately cut out errors from callback functions completely.
all the methods in this module have the simplified signature:
ES.METHOD(record, function(response){
  // do something with response

Instead, we propose using a
central error catcher. e.g:
process.on('uncaughtException', function(err) {
  console.log('ERROR: ' + err); // preferably handle errors appropriately
or, if you are using Hapi.js
we recommend using
For more on Errors, please read:


all caps
We prefer to have the METHOD names UPPERCASE because it makes them easy to spot and differentiate from your code. If you feel they are a bit "shouty" all methods are available in lowercase too; take your pick! see:

Module Name

The choice of module name was the
answer to the question:
Q: Which ElasticSearch Node Module should I use...?