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Reactive database layer with references, generators, triggers, migrations, etc.

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Meteor smart package which provides a reactive database layer with references, generators, triggers, migrations, etc. Meteor provides a great way to code in a reactive style and this package brings reactivity to your database as well. You can now define inside your application along with the rest of your program logic also how your data should be updated on any change and how various aspects of your data should be kept in sync and consistent no matter where the change comes from.

Implemented features are: * reactive references between documents * reactive reverse references between documents * reactive auto-generated fields from other fields * reactive triggers * migrations

Planned features are: * versioning of all changes to documents * integration with full-text search * strict-typed schema validation

Adding this package to your Meteor application adds the

object into the global scope.

Both client and server side.


meteor add peerlibrary:peerdb

Additional packages


Instead of Meteor collections with PeerDB you are defining PeerDB documents by extending

. Internally it defines a Meteor collection, but also all returned documents are then an instance of that PeerDB documents class.

Minimal definition:

class Person extends Document
    name: 'Person'

This would create in your database a MongoDB collection called

must match the class name.
is used for PeerDB and in addition you can define arbitrary class or object methods for your document which will then be available on documents returned from the database:
class Person extends Document
  # Other fields:
  #   username
  #   displayName
  #   email
  #   homepage

@Meta name: 'Person'

Class methods

@verboseName: -> @Meta._name.toLowerCase()

@verboseNamePlural: -> "#{ @verboseName() }s"

Instance method

getDisplayName: -> @displayName or @username

You can also wrap existing Meteor collections:

class User extends Document
    name: 'User'
    collection: Meteor.users

And if you need to access the internal or wrapped collection you can do that by:

  username: 1


PeerDB provides an alternative to Meteor collections query methods. You should be using them to access documents. You can access them through the

property of your document class. For example:
Person.documents.find({}).forEach (person, i, cursor) =>
  console.log person.constructor.verboseName(), person.getDisplayName()



The functions and arguments available are the same as those available for Meteor collections, with the addition of:

  • .documents.exists(query, options)
    – efficient check if any document matches given
  • .documents.bulkInsert(arrayOfDocuments, [options], callback)
    – insert multiple documents in bulk, returning the list of IDs and calling an optional callback

has a special handling of references to minimize issues of loading documents referencing documents which are yet to be inserted. By default, first, all documents are inserted with all optional references delayed. This means, all optional references are first omitted, and then all documents are updated by the second query, setting values for all optional references. Reference fields inside arrays are always delayed. Optional
object accepts field: *
– a list of paths of optional reference fields which should not be delayed

In a similar way we extend the cursor returned from

with an
method which operates similar to the
method, only that it is more efficient:

gives you back document metadata and
give you access to all documents.

All this is just an easy way to define documents and collections in a unified fashion, but it becomes interesting when you start defining relations between documents.


In the traditional SQL world of relational databases you do joins between related documents every time you read them from the database. This makes reading slower, your database management system is redoing the same computation of joins for every read, and also horizontal scaling of a database to many instances is harder because every read might potentially have to talk to other instances.

NoSQL databases like MongoDB remove relations between documents and leave it to users to resolve relations on their own. This often means fetching one document, observing which other documents it references, and fetching those as well. Because each of those documents are stand-alone and static, it is relatively easy and quick for a database management system like MongoDB to find and return them. Such an approach is quick and it scales easily, but the downside is the multiple round trips you have to do in your code to get all documents you are interested in. Those round trips become even worse when those queries are coming over the Internet from Meteor client code, because Internet latency is much higher.

For a general case you can move this fetching of related documents to the server side into Meteor publish functions by using libraries like meteor-related. It provides an easy way to fetch related documents reactively, so when dependencies change, your published documents will be updated accordingly. While latency to your database instances is hopefully better on your server, we did not really improve much from the SQL world: you are effectively recomputing joins and now even in a much less efficient way, especially if you are reading multiple documents at the same time.

Luckily, in many cases we can observe that we are mostly interested only in few fields of a related document, again and again. Instead of recomputing joins every time we read, we could use MongoDB's sub-documents feature to embed those fields along with the reference. Instead of just storing the

of a related document, we could store also those few often used fields. For example, if you are displaying blog posts, you want to display the author's name together with the blog post. You won't really need only the blog post without the author name. An example blog post document could then look like:
  "_id": "frqejWeGWjDTPMj7P",
  "body": "A simple blog post",
  "author": {
    "_id": "yeK7R5Lws6MSeRQad",
    "username": "wesley",
    "displayName": "Wesley Crusher"
  "subscribers": [
      "_id": "k7cgWtxQpPQ3gLgxa"
      "_id": "KMYNwr7TsZvEboXCw"
      "_id": "tMgj8mF2zF3gjCftS"
  "reviewers": [
      "_id": "tMgj8mF2zF3gjCftS",
      "username": "deanna",
      "displayName": "Deanna Troi"

Great! Now we have to fetch only this one document and we have everything needed to display a blog post. It is easy for us to publish it with Meteor and use it as any other document, with direct access to author's fields.

Now, storing the author's name along with every blog post document brings an issue. What if user changes their name? Then you have to update all those fields in documents referencing the user. So you would have to make sure that anywhere in your code where you are changing the name, you are also updating fields in references. What about changes to the database coming from outside of your code? Here is when PeerDB comes into action. With PeerDB you define those references once and then PeerDB makes sure they stay in sync. It does not matter where the changes come from, it will detect them and update fields in referenced sub-documents accordingly.

If we have two documents:

class Person extends Document
  # Other fields:
  #   username
  #   displayName
  #   email
  #   homepage

@Meta name: 'Person'

class Post extends Document

Other fields:


@Meta name: 'Post' fields: -> # We can reference other document author: @ReferenceField Person, ['username', 'displayName'] # Or an array of documents subscribers: [@ReferenceField Person] reviewers: [@ReferenceField Person, ['username', 'displayName']]

We are using

argument to define references.

In the above definition, the

field will be a subdocument containing
(always added) and the
fields. If the
field in the referenced
document is changed, the
field in all related
documents will be automatically updated with the new value for the
Person.documents.update 'tMgj8mF2zF3gjCftS',
    displayName: 'Deanna Troi-Riker'

Returns "Deanna Troi-Riker"


Returns "Deanna Troi-Riker", sub-documents are objectified into document instances as well



field is an array of references to
documents, where every element in the array will be a subdocument containing only the

Circular references are possible as well:

class CircularFirst extends Document
  # Other fields:
  #   content

@Meta name: 'CircularFirst' fields: -> # We can reference circular documents second: @ReferenceField CircularSecond, ['content']

class CircularSecond extends Document

Other fields:


@Meta name: 'CircularSecond' fields: -> # But of course one should not be required so that we can insert without warnings first: @ReferenceField CircularFirst, ['content'], false

If you want to reference the same document recursively, use the string

as an argument to
class Recursive extends Document
  # Other fields:
  #   content

@Meta name: 'Recursive' fields: -> other: @ReferenceField 'self', ['content'], false

All those references between documents can be tricky as you might want to reference documents defined afterwards and JavaScript symbols might not even exist yet in the scope, and PeerDB works hard to still allow you to do that. But to make sure all symbols are correctly resolved you should call

after all your definitions. The best is to put it in the filename which is loaded last.

One more example to show use of nested objects:

class ACLDocument extends Document
    name: 'ACLDocument'
    fields: ->
        admins: [@ReferenceField User]
        editors: [@ReferenceField User]

You can also do:

class ACLDocument extends Document
  # Each permission object inside "permissions" could have also
  # timestamp and permission type fields.

@Meta name: 'ACLDocument' fields: -> permissions: [ user: @ReferenceField User grantor: @ReferenceField User, [], false ]

accepts the following arguments:
  • targetDocument
    – target document class, or
  • fields
    – list of fields to sync in a reference's sub-document; instead of a field name you can use a MongoDB projection as well, like
    emails: {$slice: 1}
  • required
    – should the reference be required (default) or not. If required, when the referenced document is removed, this document will be removed as well. If not required, the reference will be set to
  • reverseName
    – name of a field for a reverse reference; specify to enable a reverse reference
  • reverseFields
    – list of fields to sync for a reference reference

What are reverse references?

Reverse references

Sometimes you want also to have easy access to information about all the documents referencing a given document. For example, for each author you might want to have a list of all blog posts they wrote, as part of their document.

class Post extends Post
    name: 'Post'
    replaceParent: true
    fields: (fields) -> = @ReferenceField Person, ['username', 'displayName'], true, 'posts'

We redefine the

document and replace it with a new definition which enables reverse references for the
field. Now
  "_id": "yeK7R5Lws6MSeRQad",
  "username": "wesley",
  "displayName": "Wesley Crusher",
  "email": "[email protected]",
  "homepage": "https://gww.enterprise.starfleet/~wesley/",
  "posts": [
      "_id": "frqejWeGWjDTPMj7P"

Auto-generated fields

Sometimes you need fields in a document which are based on other fields. PeerDB allows you an easy way to define such auto-generated fields:

class Post extends Post
  # Other fields:
  #   title

@Meta name: 'Post' replaceParent: true generators: (generators) -> generators.slug = @GeneratedField 'self', ['title'], (fields) -> unless fields.title [fields._id, undefined] else [fields._id, "prefix-#{ fields.title.toLowerCase() }-suffix"] generators

The last argument of

is a function which receives an object populated with values based on the list of fields you are interested in. In the example above, this is one field named
from the
collection. The
field is always available in
. Generator function receives just
when document containing fields is being removed. Otherwise it receives all fields requested. Generator function should return two values, a selector (often just the ID of a document) and a new value. If the value is undefined, the auto-generated field is removed. If the selector is undefined, nothing is done.

You can define auto-generated fields across documents. Furthermore, you can combine reactivity. Maybe you want to also have a count of all posts made by a person?

class Person extends Person
    name: 'Person'
    replaceParent: true
    generators: (generators) ->
      generators.postsCount = @GeneratedField 'self', ['posts'], (fields) ->
        [fields._id, fields.posts?.length or 0]


You can define triggers which are run every time any of the specified fields changes:

class Post extends Post
  # Other fields:
  #   updatedAt

@Meta name: 'Post' replaceParent: true triggers: -> updateUpdatedAt: @Trigger ['title', 'body'], (newDocument, oldDocument) -> # Don't do anything when document is removed return unless newDocument?._id

    timestamp = new Date()
      _id: newDocument._id
        $lt: timestamp
        updatedAt: timestamp

The return value is ignored.

can be
when a document has been removed or added, respectively. Triggers are useful when you want arbitrary code to be run when fields change. This could be implemented directly with observe, but triggers simplify that and provide an alternative API in the PeerDB spirit.

Why we are using a trigger here and not an auto-generated field? The main reason is that we want to ensure

really just increases, so a more complicated update query is needed. Additionally, reference fields and auto-generated fields should be without side-effects and should be allowed to be called at any time. This is to ensure that we can re-sync any broken references as needed. If you would use an auto-generated field, it could be called again at a later time, updating
to a later time without any content of a document really changing.

PeerDB does not really re-sync any broken references (made while your Meteor application was not running) automatically. If you believe such references exist (eg., after a hard crash of your application), you can trigger re-syncing by calling

. All references will be resynced and all auto-generated fields rerun. But not triggers. It is a quite heavy operation.

Abstract documents and

You can define abstract documents by setting the

flag to
. Such documents will not create a MongoDB collection. They are useful to define common fields and methods you want to reuse in multiple documents.

We skimmed over

before. You should set it to
when you are defining a document with the same name as a document you are extending (parent). It is a kind of a sanity check that you know what you are doing and that you are promising you are not holding a reference to the extended (and replaced) document somewhere and you expect it to work when using it. How useful
really is, is a good question, but it allows you to define a common (client and server side) document and then augment it on the server side with server-specific code.


If you would like to run some code after Meteor startup, but before observers are enabled, you can use

to register a callback. If you would like to run some code after Meteor startup and after observers are enabled, you can use
to register a callback.



As your application grows you might want to run specialized Meteor instances just to do PeerDB reactive MongoDB queries. To distribute PeerDB load, configure the number of PeerDB instances using the

environment variable. Suggested setting is that your web-facing instances disable PeerDB by setting
to 0, and then you have dedicated PeerDB instances.


If you are running multiple PeerDB instances, which instance is this? It is zero-based index so if you configured

, you have to have two instances, one with
and another with


When running multiple instances you want to connect them all to the same database. You have to configure both normal MongoDB connection and also the oplog connection. You can use your own MongoDB instance or connect to one provided by running Meteor in development mode. In the latter case the recommended way is that one web-facing instance runs MongoDB and all other instances connect to that MongoDB.



See tests for many examples. See document definitions in PeerLibrary for real-world definitions.

Related projects

  • matb33:collection-hooks – provides an alternative way to attach additional program logic on changes to your data, but it hooks into collection API methods so if a change comes from the outside, hooks are not called; additionally, collection API methods are delayed for the time of all hooks to be executed while in PeerDB hooks run in parallel in or even in a separate process (or processes), allowing your code to return quickly while PeerDB assures that data will be eventually consistent (this has a downside of course as well, so if you do not want that API calls return before all hooks run,
    might be more suitable for you)
  • peerlibrary:meteor-related – while PeerDB provides an easy way to embed referenced documents as subdocuments, it requires that those relations are the same for all users; if you want dynamic relations between documents,
    provides an easy way to fetch related documents reactively on the server side, so when dependencies change, your published documents will be updated accordingly
  • herteby:denormalize – it does similar denormalization, but uses
    hooks instead reactivity to maintained denormalization, moreover, it looks like
    is much more limited in features than this package, which provides, e.g., also wrapping of documents into JavaScript objects with methods, generators, and reverse fields

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