The Elasticsearch connector enables LoopBack applications to connect to Elasticsearch data sources.


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Basic Elasticsearch datasource connector for Loopback.

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  1. lib directory has the entire source code for this connector
    1. this is what gets downloaded to your node_modules folder when you run npm install loopback-connector-es --save --save-exact
  2. examples directory has a loopback app which uses this connector
    1. this is not published to NPM, it is only here for demo purposes
      1. it will not be downloaded to your node_modules folder!
      2. similarly the examples/server/datasources.json and examples/server/datasources.<env>.js files are there for this demo app to use
      3. you can copy their content over to <yourApp>/server/datasources.json or <yourApp>/server/datasources.<env>.js if you want and edit it there but don’t start editing the files inside examples/server itself and expect changes to take place in your app!
  3. test directory has unit tests
    1. it does not reuse the loopback app from the examples folder
    2. instead, loopback and ES/datasource are built and injected programatically
    3. this directory is not published to NPM.
      1. Refer to .npmignore if you’re still confused about what’s part of the published connector and what’s not.
  4. You will find the datasources.json files in this repo mention various configurations:
    1. elasticsearch-ssl
    2. elasticsearch-plain
    3. db
    4. You don’t need them all! They are just examples to help you see the various ways in which you can configure a datasource. Delete the ones you don’t need and keep the one you want. For example, most people will start off with elasticsearch-plain and then move on to configuring the additional properties that are exemplified in elasticsearch-ssl. You can mix & match if you’d like to have mongo and es and memory, all three! These are basics of the “connector” framework in loooback and not something we added.
  5. Don’t forget to edit your model-config.json file and point the models at the dataSource you want to use.

Install this connector in your loopback app

cd <yourApp>
npm install loopback-connector-es --save --save-exact

Configuring connector


  • host: Elasticsearch engine host address.
  • port: Elasticsearch engine port.
  • name: Connector name.
  • connector: Elasticsearch driver.
  • index: Search engine specific index.
  • apiVersion: specify the major version of the Elasticsearch nodes you will be connecting to.
  • mappings: an array of elasticsearch mappings for your various loopback models.
    • if your models are spread out across different indexes then you can provide an additional index field as an override for your model
    • if you don’t want to use type:ModelName by default, then you can provide an additional type field as an override for your model


  • log: sets elasticsearch client’s logging, you can refer to the docs here
  • defaultSize: total number of results to return per page.
  • refreshOn optional array with method names you want to set refresh option as true
  • requestTimeout: this value is in milliseconds
  • ssl: useful for setting up a secure channel
  • protocol: can be http or https (http is the default if none specified) … must be https if you’re using ssl
  • auth: useful if you have access control setup via services like es-jetty or found or shield
  • amazonES: configuration for http-aws-es NOTE: The package needs to be installed in your project. Its not part of this Connector.


  1. Edit datasources.json and set:

     "db": {
         "connector": "es",
         "name": "<name>",
         "index": "<index>",
         "hosts": [
             "protocol": "http",
             "host": "",
             "port": 9200,
             "auth": "username:password"
         "apiVersion": "<apiVersion>",
         "refreshOn": ["save","create", "updateOrCreate"],
         "log": "trace",
         "defaultSize": <defaultSize>,
         "requestTimeout": 30000,
         "ssl": {
                 "ca": "./../cacert.pem",
                 "rejectUnauthorized": true
         "amazonES": {
                 "region": "us-east-1",
                 "accessKey": "AKID",
                 "secretKey": "secret"
         "mappings": [
             "name": "UserModel",
             "properties": {
                 "realm": {"type": "string", "index" : "not_analyzed" },
                 "username": {"type": "string", "index" : "not_analyzed" },
                 "password": {"type": "string", "index" : "not_analyzed" },
                 "email": {"type": "string", "analyzer" : "email" }
             "name": "CoolModel",
             "index": <useSomeOtherIndex>,
             "type": <overrideTypeName>,
             "properties": {
                 "realm": {"type": "string", "index" : "not_analyzed" },
                 "username": {"type": "string", "index" : "not_analyzed" },
                 "password": {"type": "string", "index" : "not_analyzed" },
                 "email": {"type": "string", "analyzer" : "email" }
         "settings": {
             "analysis": {
                 "filter": {
                     "email": {
                         "type": "pattern_capture",
                         "preserve_original": 1,
                         "patterns": [
                 "analyzer": {
                     "email": {
                         "tokenizer": "uax_url_email",
                         "filter": ["email", "lowercase", "unique"]
  2. You can peek at /examples/server/datasources.json for more hints.

About the example app

  1. The examples directory contains a loopback app which uses this connector.
  2. You can point this example at your own elasticsearch instance or use the quick instances provided via docker.

Run both example and ES in docker

As a developer, you may want a short lived ES instance that is easy to tear down when you’re finished dev testing. We recommend docker to facilitate this.

Pre-requisites You will need docker-engine and docker-compose installed on your system.


  • Set desired versions for node and Elasticsearch
    • here are the valid values to use for Node
    • here are the valid values to use for Elasticsearch ```

      combination of node v0.10.46 with elasticsearch v1

      export NODE_VERSION=0.10.46 export ES_VERSION=1 echo ‘NODE_VERSION’ $NODE_VERSION && echo ‘ES_VERSION’ $ES_VERSION

similarly feel free to try relevant combinations:

of node v0.10.46 with elasticsearch v2

of node v0.12 with elasticsearch v2

of node v0.4 with elasticsearch v2

of node v5 with elasticsearch v2

elasticsearch v5 will probably not work as there isn’t an elasticsearch client for it, as of this writing


- Run the setup with `docker-compose` commands.

git clone myEsConnector cd myEsConnector/examples npm install docker-compose up

- Visit `localhost:3000/explorer` and you will find our example loopback app running there.

### Run example locally and ES in docker

1. Empty out `examples/server/datasources.json` so that it only has the following content remaining: `{}`
1. Set the `NODE_ENV` environment variable on your local/host machine
    1. Set the environment variable `NODE_ENV=sample-es-plain-1` if you want to use `examples/server/datasources.sample-es-plain-1.js`
    1. Set the environment variable `NODE_ENV=sample-es-plain-2` if you want to use `examples/server/datasources.sample-es-plain-2.js`
    1. Set the environment variable `NODE_ENV=sample-es-ssl-1` if you want to use `examples/server/datasources.sample-es-ssl-1.js`
        1. a sample docker instance for this hasn't been configured yet, so it doesn't work out-of-the-box, use it only as readable (not runnable) reference material for now
    1. You can configure your own `datasources.json` or `datasources.<env>.js` based on what you learn from these sample files.
        1. Technically, to run the example, you don't need to set `NODE_ENV` **if you won't be configuring via the `.<env>.js` files** ... configuring everything within `datasources.json` is perfectly fine too. Just remember that you will lose the ability to have inline comments and will have to use double-quotes if you stick with `.json`
1. Start elasticsearch version 1.x and 2.x using:

    git clone myEsConnector
    cd myEsConnector
    docker-compose -f docker-compose-for-tests.yml up

    # in another terminal window or tab
    cd myEsConnector/examples
    npm install
    DEBUG=boot:test:* node server/server.js
1. Visit `localhost:3000/explorer` and you will find our example loopback app running there.

### Run example locally

1. Install dependencies and start the example server

    git clone myEsConnector
    cd myEsConnector/examples
    npm install
2. [Configure the connector](#configuring-connector)
    * Don't forget to create an index in your ES instance: `curl -X POST https://username:[email protected]/shakespeare`
    * If you mess up and want to delete, you can use: `curl -X DELETE https://username:[email protected]/shakespeare`
    * Don't forget to set a [valid value]( for `apiVersion` field in `examples/server/datasources.json` that matches the version of ES you are running.
3. Set up a `cacert.pem` file for communicating securely (https) with your ES instance. Download the certificate chain for your ES server using this **sample** (will need to be edited to *use* your provider) command:

    cd myEsConnector
    openssl s_client -connect -showcerts | tee cacert.pem
    1. The command may not self terminate so you may need to use `ctrl+c`
    2. It will be saved at the base of your cloned project
    3. Sometimes extra data is added to the file, you should delete everything after the following lines:

    No client certificate CA names sent
4. Run:

    cd myEsConnector/examples
    DEBUG=boot:test:* node server/server.js
    * The `examples/server/boot/boot.js` file will automatically populate data for UserModels on your behalf when the server starts.
5. Open this URL in your browser: [http://localhost:3000/explorer](http://localhost:3000/explorer)
    * Try fetching all the users via the rest api console
    * You can dump all the data from your ES index, via cmd-line too: `curl -X POST username:[email protected]/shakespeare/_search -d '{"query": {"match_all": {}}}'`
6. To test a specific filter via GET method, use for example: `{"q" : "friends, romans, countrymen"}`

## How to achieve Instant search

From version 1.3.4, `refresh` option is added which support's instant search after `create` and `update`. This option is configurable and one can activate or deactivate it according to their need. `By default refresh is true` which makes response to come only after documents are indexed(searchable).
To know more about `refresh` go through this [article](

* [Related Issue](
* [Related PR](

### Ways to configure refresh
**Datasource File:** Pass `refreshOn` array from datasource file including methods name in which you want this to be `true`
"es": {
    "name": "es",
    "refreshOn": ["save","create", "updateOrCreate"],
    ..... ``` **Model.json file:** Configurable on per model and operation level (`true`, `false`, `wait_for`) ```
"elasticsearch": {
     "create": {
         "refresh": false
     "destroy": {
         "refresh": false
     "destroyAll": {
         "refresh": "wait_for"
} ``` ###### NOTE:- *While a refresh is useful, it still has a performance cost. A manual refresh can be useful, but avoid manual refresh every time you index a document in production; it will hurt your performance. Instead, your application needs to be aware of the near real-time nature of Elasticsearch and make allowances for it.*


  1. Do you have both elasticsearch-ssl and elasticsearch-plain in your datasources.json file? You just need one of them (not both), based on how you’ve setup your ES instance.
  2. Did you forget to set model-config.json to point at the datasource you configured? Maybe you are using a different or misspelled name than what you thought you had!
  3. Did you forget to set a valid value for apiVersion field in datasources.json that matches the version of ES you are running?
  4. Maybe the version of ES you are using isn’t supported by the client that this project uses. Try removing the elasticsearch sub-dependency from <yourApp>/node_modules/loopback-connector-es/node_modules folder and then install the latest client:
    1. cd <yourApp>/node_modules/loopback-connector-es/node_modules
    2. then remove the elasticsearch folder
      1. unix/mac quickie: rm -rf elasticsearch
    3. npm install --save --save-exact
    4. to “academically” prove to yourself that this will work with the new install:
      1. on unix/mac you can quickly dump the supported versions to your terminal with: cat elasticsearch/package.json | grep -A 5 supported_es_branches
      2. on other platforms, look into the elasticsearch/package.json and search for the supported_es_branches json block.
    5. go back to yourApp’s root directory
      1. unix/mac quickie: cd <yourApp>
    6. And test that you can now use the connector without any issues!
    7. These changes can easily get washed away for several reasons. So for a more permanent fix that adds the version you want to work on into a release of this connector, please look into Contributing.


  1. You can edit test/resource/datasource-test.json to point at your ES instance and then run npm test
  2. If you don’t have an ES instance and want to leverage docker based ES instances then:
    1. If you want to run all tests across all versions in one go, then:
      1. Run docker-compose -f docker-compose-for-testing-all.yml up
      2. Then run npm test
      3. When you’re finished and want to tear down the docker instances, run: docker-compose -f docker-compose-for-testing-all.yml down
    2. You can test a specific version of elasticsearch if you want
      1. elasticsearch version 1.x
        1. Run docker-compose -f docker-compose-for-testing-v1.yml up
        2. Then run npm run testv1
          1. To run tests with additional logging, use:
            1. DEBUG=test:es-v1:* npm run testv1
            2. DEBUG=test:es-v1:*,loopback:connector:elasticsearch npm run testv1
          2. Troubleshoot test with node-inspector if the level of details is still not enough:
            1. npm run testv1 -- --debug-brk
            2. DEBUG=test:es-v1:* npm run testv1 -- --debug-brk
            3. DEBUG=test:es-v1:*,loopback:connector:elasticsearch npm run testv1 -- --debug-brk
        3. When you’re finished and want to tear down the docker instances, run: docker-compose -f docker-compose-for-testing-v1.yml down
      2. elasticsearch version 2.x
        1. Run docker-compose -f docker-compose-for-testing-v2.yml up
        2. Then run npm run testv2
          1. To run tests with additional logging, use:
            1. DEBUG=test:es-v2:* npm run testv2
            2. DEBUG=test:es-v2:*,loopback:connector:elasticsearch npm run testv2
          2. Troubleshoot test with node-inspector if the level of details is still not enough:
            1. npm run testv2 -- --debug-brk
            2. DEBUG=test:es-v2:* npm run testv2 -- --debug-brk
            3. DEBUG=test:es-v2:*,loopback:connector:elasticsearch npm run testv2 -- --debug-brk
        3. When you’re finished and want to tear down the docker instances, run: docker-compose -f docker-compose-for-testing-v2.yml down
      3. elasticsearch version 5.x
        1. Run docker-compose -f docker-compose-for-testing-v5.yml up
        2. Then run npm run testv5
          1. To run tests with additional logging, use:
            1. DEBUG=test:es-v5:* npm run testv5
            2. DEBUG=test:es-v5:*,loopback:connector:elasticsearch npm run testv5
          2. Troubleshoot test with node-inspector if the level of details is still not enough:
            1. npm run testv5 -- --debug-brk
            2. DEBUG=test:es-v5:* npm run testv5 -- --debug-brk
            3. DEBUG=test:es-v5:*,loopback:connector:elasticsearch npm run testv5 -- --debug-brk
        3. When you’re finished and want to tear down the docker instances, run: docker-compose -f docker-compose-for-testing-v5.yml down


  1. Feel free to contribute via PR or open an issue for discussion or jump into the gitter chat room if you have ideas.
  2. I recommend that project contributors who are part of the team:
    1. should merge master into develop … if they are behind, before starting the feature branch
    2. should create feature branches from the develop branch
    3. should merge feature into develop then create a release branch to:
      1. update the changelog
      2. close related issues and mention release version
      3. update the readme
      4. fix any bugs from final testing
      5. commit locally and run npm-release x.x.x -m "<some comment>"
      6. merge release into both master and develop
      7. push master and develop to GitHub
  3. For those who use forks:
    1. please submit your PR against the develop branch, if possible
    2. if you must submit your PR against the master branch … I understand and I can’t stop you. I only hope that there is a good reason like develop not being up-to-date with master for the work you want to build upon.
  4. npm-release <versionNumber> -m <commit message> may be used to publish. Pubilshing to NPM should happen from the master branch. It should ideally only happen when there is something release worthy. There’s no point in publishing just because of changes to test or examples folder or any other such entities that aren’t part of the “published module” (refer to .npmignore) to begin with.


  1. How do we enable or disable the logs coming from the underlying elasticsearch client? There may be a need to debug/troubleshoot at times.
    1. Use the "log": "trace" field in your datasources file or omit it. You can refer to the detailed docs here and here
  2. How do we enable or disable the logs coming from this connector?
    1. By default if you do not set the following env variable, they are disabled: DEBUG=loopback:connector:elasticsearch
      1. For example, try running tests with and without it, to see the difference:
        1. with: DEBUG=loopback:connector:elasticsearch npm test
        2. without: npm test
  3. What are the tests about? Can you provide a brief overview?
    1. Tests are prefixed with 01 or 02 etc. in order to run them in that order by leveraging default alphabetical sorting.
    2. The 02.basic-querying.test.js file uses two models to test various CRUD operations that any connector must provide, like find(), findById(), findByIds(), updateAttributes() etc.
      1. the two models are User and Customer
      2. their ES mappings are laid out in test/resource/datasource-test.json
      3. their loopback definitions can be found in the first before block that performs setup in 02.basic-querying.test.js file … these are the equivalent of a MyModel.json in your real loopback app.
        1. naturally, this is also where we define which property serves as the id for the model and if its generated or not
  4. How do we get elasticserch to take over ID generation?
    1. An automatically generated id-like field that is maintained by ES is _uid. Without some sort of es-field-level-scripting-on-index (if that is possible at all) … I am not sure how we could ask elasticsearch to take over auto-generating an id-like value for any arbitrary field! So the connector is setup such that adding id: {type: String, generated: true, id: true} will tell it to use _uid as the actual field backing the id … you can keep using the doing abstraction and in the background _uid values are mapped to it.
    2. Will this work for any field marked as with generated: true and id: true?
      1. No! The connector isn’t coded that way right now … while it is an interesting idea to couple any such field with ES’s _uid field inside this connector … I am not sure if this is the right thing to do. If you had objectId: {type: String, generated: true, id: true} then you won’t find a real objectId field in your ES documents. Would that be ok? Wouldn’t that confuse developers who want to write custom queries and run 3rd party app against their ES instance? Don’t use obejctId, use _uid would have to be common knowledge. Is that ok?

Release notes

  • Release 1.0.6 of this connector updates the underlying elasticsearch client version to 11.0.1
  • For this connector, you can configure an index name for your ES instance and the loopback model’s name is conveniently/automatically mapped as the ES type.
  • Users must setup string fields as not_analyzed by default for predictable matches just like other loopback backends. And if more flexibility is required, multi-field mappings can be used too.

    "name" : {
        "type" : "multi_field",
        "fields" : {
            "name" : {"type" : "string", "index" : "not_analyzed"},
            "native" : {"type" : "string", "index" : "analyzed"}
    // this will treat 'George Harrison' as 'George Harrison' in a search
    User.find({order: 'name'}, function (err, users) {..}
    // this will treat 'George Harrison' as two tokens: 'george' and 'harrison' in a search
    User.find({order: 'name', where: {'name.native': 'Harrison'}}, function (err, users) {..}
  • Release 1.3.4 add’s support for updateAll for elasticsearch v-2.3 and above. To make updateAll work you will have to add below options in your elasticsearch.yml config file

     script.inline: true
     script.indexed: true on
     script.engine.groovy.inline.update: on
  • TBD
Tags: community