Waterline is a brand new kind of storage and retrieval engine.

It provides a uniform API for accessing stuff from different kinds of databases, protocols, and 3rd party APIs. That means you write the same code to get users, whether they live in MySQL, LDAP, MongoDB, or Facebook.

At the same time, Waterline aims to learn lessons and maintain the best features from both Rails' ActiveRecord and Grails' Hibernate ORMs.

Install from NPM.

$ npm install waterline

var User = Waterline.Collection.extend({

  attributes: {

    firstName: {
      type: 'string',
      required: true
    },

    lastName: {
      type: 'string',
      required: true,
    }
  }
});

Waterline was extracted from the Sails framework and is the default ORM used in Sails. For more information on using Waterline in your Sails App view the Sails Docs.

For examples of how to use with frameworks such as Express look in the Example folder.

Waterline uses the concept of an Adapter to translate a predefined set of methods into a query that can be understood by your data store. Adapters allow you to use various datastores such as MySQL, PostgreSQL, MongoDB, Redis, etc. and have a clear API for working with your model data.

It also allows an adapter to define it's own methods that don't necessarily fit into the CRUD methods defined by default in Waterline. If an adapter defines a custom method, Waterline will simply pass the function arguments down to the adapter.

NOTE: When using custom adapter methods the features of Waterline are not used. You no longer get the Lifecycle Callbacks and Validations as you would when using a defined Waterline method.

You may also supply an array of adapters and Waterline will map out the methods so they are both mixed in. It works similar to Underscore's Extend method where the last item in the array will override any methods in adapters before it. This allows you to mixin bothe traditional CRUD adapters such as MySQL with specialized adapters such as Twilio and have both types of methods available.

• PostgreSQL - 0.9+ compatible
• MySQL - 0.9+ compatible
• MongoDB - 0.9+ compatible
• Memory - 0.9+ compatible
• Disk - 0.9+ compatible
• Redis
• Riak
• IRC
• Twitter
• JSDom

A Collection is the main object used in Waterline. It defines the layout/schema of your data along with any validations and instance methods you create.

To create a new collection you extend Waterline.Collection and add in any properties you need.

Available options are

• tableName Define a custom table name to store the models
• adapters the name of the adapter you would like to use for this collection
• schema Set schema true/false to only allow fields defined in attributes to be saved. Only for schemaless adapters.
• attributes A hash of attributes to be defined for a model
• autoCreatedAt and autoUpdateddAt Set false to prevent creating createdAt and updatedAt properties in your model
• autoPK Set false to prevent creating id. By default id will be created as index with auto increment
• lifecyle callbacks
• anyother class method you define!

The following attribute types are currently available:

• string
• text
• integer
• float
• date
• time
• datetime
• boolean
• binary
• array
• json

var User = Waterline.Collection.extend({

  // Define a custom table name
  tableName: 'user',

  // Set schema true/false for adapters that support schemaless
  schema: true,

  // Define an adapter to use
  adapter: 'postgresql',

  // Define attributes for this collection
  attributes: {

    firstName: {
      type: 'string',

      // also accepts any validations
      required: true
    },

    lastName: {
      type: 'string',
      required: true,
      maxLength: 20
    },

    email: {

      // Special types are allowed, they are used in validations and
      // set as a string when passed to an adapter
      type: 'email',

      required: true
    },

    age: {
      type: 'integer',
      min: 18
    },

    // You can also define instance methods here
    fullName: function() {
      return this.firstName + ' ' + this.lastName
    }
  },

  /**
   * Lifecycle Callbacks
   *
   * Run before and after various stages:
   *
   * beforeValidation
   * afterValidation
   * beforeUpdate
   * afterUpdate
   * beforeCreate
   * afterCreate
   * beforeDestroy
   * afterDestroy
   */

  beforeCreate: function(values, cb) {

    // an example encrypt function defined somewhere
    encrypt(values.password, function(err, password) {
      if(err) return cb(err);

      values.password = password;
      cb();
    });
  },

  // Class Method
  doSomething: function() {
    // do something here
  }

});

Now that a collection is defined we can instantiate it and begin executing queries against it. All Collections take options and callback arguments.

Options will be made up of:

• tableName, used if not defined in a Collection definition
• adapters object that specifies each adapter, either custom definitions or from NPM

var postgres = require('sails-postgresql');

new User({ tableName: 'foobar', adapters: { postgresql: postgres }}, function(err, Model) {

  // We now have an instantiated collection to execute queries against
  Model.find()
  .where({ age: 21 })
  .limit(10)
  .exec(function(err, users) {
    // Now we have an array of users
  });

});

Each result that gets returned from a Waterline query will be an instance of Model. This will add in any instance methods defined in your collection along with some CRUD helper methods. View Core Instance Methods to see how the methods are implemented.

Default CRUD instance methods:

• save
• destroy
• toObject
• toJSON

If you would like to filter records and remove certain attributes you can override the toJSON method like so:

var user = Waterline.Collection.extend({

  attributes: {
    name: 'string',
    password: 'string',

    // Override toJSON instance method
    toJSON: function() {
      var obj = this.toObject();
      delete obj.password;
      return obj;
    }
  }
});

// Then on an instantiated user:
user.find({ id: 1}).exec(function(err, model) {
  return model.toJSON(); // will return only the name
});

Queries can be run with either a callback interface or with a deferred object. For building complicated queries the deferred object method is the best choice. For convenience, promises are supported by default.

Callback Method

User.findOne({ id: 1 }, function(err, user) {
  // Do stuff here
});

Deferred Object Method

User.find()
.where({ id: { '>': 100 }})
.where({ age: 21 })
.limit(100)
.sort('name')
.exec(function(err, users) {
  // Do stuff here
});

Promises

User.findOne()
.where({ id: 2 })
.then(function(user){
    var comments = Comment.find({userId: user.id}).then(function(comments){
        return comments;
    });
    return [user.id, user.friendsList, comments];
}).spread(function(userId, friendsList, comments){
    // Promises are awesome!
}).fail(function(err){
    // An error occured
})

Promises use the Q library, so anything you do after the first then call (or spread, or fail), will be a complete Q promise object. Remember, you must end the query somehow (by calling then or one of the other functions) in order to complete the database request.

Each of the following basic methods are available by default on a Collection instance.

• findOne
• find
• create
• update
• destroy
• count

In addition you also have the following helper methods:

• createEach
• findOrCreateEach
• findOrCreate
• findOneLike
• findLike
• startsWith
• endsWith
• contains

Based on your Collection attributes you also have dynamic finders. So given a name attribute the following queries will be available:

• findOneByName
• findOneByNameIn
• findOneByNameLike
• findByName
• findByNameIn
• findByNameLike
• countByName
• countByNameIn
• countByNameLike
• nameStartsWith
• nameEndsWith
• nameContains

Validations are handled by Anchor which is based off of Node Validate and supports most of the properties in node-validate. For a full list of validations see: Anchor Validations.

Validations are defined directly in you Collection attributes. In addition you may set the attribute type to any supported Anchor type and Waterline will build a validation and set the schema type as a string for that attribute.

var User = Waterline.Collection.extend({

  attributes: {

    firstName: {
      type: 'string',
      required: true,
      minLength: 5,
      maxLength: 15
    },

    lastName: {
      type: 'string',
      required: true,
      minLength: 5,
      maxLength: 100
    },

    age: {
      type: 'integer',
      after: '12/12/2001'
    }
  }
});

You can define your own types and their validation with the types hash

var User = Waterline.Collection.extend({
  types: {
    point: function(latlng){
     return latlng.x && latlng.y
    }
  },
  
  attributes: {
    firstName: {
      type: 'string',
      required: true,
      minLength: 5,
      maxLength: 15
    },

    location: {
      //note, that the base type (json) still has to be define
      type: 'json',
      point: true
    }
  }
});

You can add an index property to any attribute to create an index if your adapter supports it. This comes in handy when performing repeated queries against a key.

var User = Waterline.Collection.extend({

  attributes: {

    serviceID: {
      type: 'integer',
      index: true
    }
  }
});

Currently Waterline doesn't support multi-column indexes in the attributes definition. If you would like to build any sort of special index you will still need to build that manually. Also note when adding a unique property to an attribute an index will automatically be created for that attribute so there is no need to specifiy it.

There is currently an issue with adding indexes to string fields. Because Waterline performs it's queries in a case insensitive manner we are unable to use the index on a string attribute. There are some workarounds being discussed but nothing is implemented so far. This will be updated in the near future to fully support indexes on strings.

Lifecycle callbacks are functions you can define to run at certain times in a query. They are useful for mutating data before creating or generating properties before they are validated.

Callbacks run on Create

• beforeValidation / fn(values, cb)
• afterValidation / fn(values, cb)
• beforeCreate / fn(values, cb)
• afterCreate / fn(newlyInsertedRecord, cb)

Callbacks run on Update

• beforeValidation / fn(valuesToUpdate, cb)
• afterValidation / fn(valuesToUpdate, cb)
• beforeUpdate / fn(valuesToUpdate, cb)
• afterUpdate / fn(updatedRecord, cb)

Callbacks run on Destroy

• beforeDestroy / fn(criteria, cb)
• afterDestroy / fn(cb)

All tests are written with mocha and should be run with npm:

  $ npm test