feathers-elasticsearch is a database adapter for Elasticsearch. This adapter is not using any ORM, it is dealing with the database directly through the elasticsearch.js Client.

$ npm install --save elasticsearch feathers-elasticsearch

Getting Started

The following bare-bones example will create a messages endpoint and connect to a local messages type in the test index in your Elasticsearch database:

const elasticsearch = require('elasticsearch');
const feathers = require('feathers');
const service = require('feathers-elasticsearch');

app.use('/messages', service({
  Model: new elasticsearch.Client({
    host: 'localhost:9200',
    apiVersion: '5.0'
  elasticsearch: {
    index: 'test',
    type: 'messages'


The following options can be passed when creating a new Elasticsearch service:

  • Model (required) - The Elasticsearch client instance.
  • elasticsearch (required) - Configuration object for elasticsearch requests. The required properties are index and type. Apart from that you can specify anything that can be passed to all requests going to Elasticsearch. Another recognised property is refresh which is set to false by default. Anything else use at your own risk.
  • id (default: '_id') [optional] - The id property of your documents in this service.
  • meta (default: '_meta') [optional] - The meta property of your documents in this service. The meta field is an object containing elasticsearch specific information, e.g. _score, _type, _index, and so forth.
  • paginate [optional] - A pagination object containing a default and max page size (see the Pagination chapter).

Complete Example

Here's an example of a Feathers server that uses feathers-elasticsearch.

const feathers = require('feathers');
const rest = require('feathers-rest');
const hooks = require('feathers-hooks');
const bodyParser = require('body-parser');
const errorHandler = require('feathers-errors/handler');
const service = require('feathers-elasticsearch');
const elasticsearch = require('elasticsearch');

const messageService = service({
  Model: new elasticsearch.Client({
    host: 'localhost:9200',
    apiVersion: '5.0'
  paginate: {
    default: 10,
    max: 50
  elasticsearch: {
    index: 'test',
    type: 'messages'

// Initialize the application
const app = feathers()
  // Needed for parsing bodies (login)
  .use(bodyParser.urlencoded({ extended: true }))
  // Initialize your feathers plugin
  .use('/messages', messageService)


console.log('Feathers app started on');

You can run this example by using npm start and going to localhost:3030/messages. You should see an empty array. That's because you don't have any messages yet but you now have full CRUD for your new message service!

Supported Elasticsearch versions

feathers-elasticsearch is currently tested on Elasticsearch 2.4, 5.0 and 5.1. The lowest version supported is 2.4, however that does not mean it wouldn't work fine on anything lower than 2.4.


Updating and deleting by query

Elasticsearch is special in many ways. For example, the "update by query" API is still considered experimental and so is the "delete by query" API introduced in Elasticsearch 5.0.

Just to clarify - update in Elasticsearch is an equivalent to patch in feathers. I will use patch from now on, to set focus on the feathers side of the fence.

Considering the above, our implementation of path / remove by query uses combo of find and bulk patch / remove, which in turn means for you:

  • Standard pagination is taken into account for patching / removing by query, so you have no guarantee that all existing documents matching your query will be patched / removed.
  • The operation is a bit slower than it could potentially be, because of the two-step process involved.

Considering, however that elasticsearch is mainly used to dump data in it and search through it, I presume that should not be a great problem.

Search visibility

Please be aware that search visibility of the changes (creates, updates, patches, removals) is going to be delayed due to Elasticsearch index.refresh_interval setting. You may force refresh after each operation by setting the service option elasticsearch.refresh as decribed above but it is highly discouraged due to Elasticsearch performance implications.

In the first version of feathers-elasticsearch full texts search has not been implemented yet. It is coming soon. It is very important feature and it sits at the top of my TODO list.

Performance considerations

None of the data mutating operations in Elasticsearch v2.4 (create, update, patch, remove) returns the full resulting document, therefore I had to resolve to using get as well in order to return complete data. This solution is of course adding a bit of an overhead, although it is also compliant with the standard behaviour expected of a feathers database adapter.

The conceptual solution for that is quite simple. This behaviour will be configurable through a lean switch allowing to get rid of those additional gets should they be not needed for your application. This feature will be added soon as well.

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