Search on multiple collections in MongoDB

This answer is outdated. Since version 3.2, MongoDB has limited support for left outer joins with the $lookup aggregation operator

MongoDB does not do queries which span multiple collections - period. When you need to join data from multiple collections, you have to do it on the application level by doing multiple queries.

1. Query collection A
2. Get the secondary keys from the result and put them into an array
3. Query collection B passing that array as the value of the $in-operator
4. Join the results of both queries programmatically on the application layer

Having to do this should be rather the exception than the norm. When you frequently need to emulate JOINs like that, it either means that you are still thinking too relational when you design your database schema or that your data is simply not suited for the document-based storage concept of MongoDB.

You'll find MongoDB easier to understand if you take a denormalized approach to schema design. That is, you want to structure your documents the way the requesting client application understands them. Essentially, you are modeling your documents as domain objects with which the applicaiton deals. Joins become less important when you model your data this way. Consider how I've denormalized your data into a single collection:

{  
    _id: 1, 
    first_name: 'Bill', 
    last_name: 'Gates', 
    suburb: 'Suburb A',
    state: 'LA',
    child : [ 3 ]
}

{ 
    _id: 2, 
    first_name: 'Steve', 
    last_name: 'Jobs', 
    suburb: 'Suburb C',
    state 'NY',
    child: [ 4 ] 
}
{ 
    _id: 3, 
    first_name: 'Little Billy', 
    last_name: 'Gates',
    suburb: 'Suburb A',
    state: 'LA',
    parent : [ 1 ]
}

{
    _id: 4, 
    first_name: 'Little Stevie', 
    last_name: 'Jobs'
    suburb: 'Suburb C',
    state 'NY',
    parent: [ 2 ]
}

The first advantage is that this schema is far easier to query. Plus, updates to address fields are now consistent with the individual Person entity since the fields are embedded in a single document. Notice also the bidirectional relationship between parent and children? This makes this collection more than just a collection of individual people. The parent-child relationships mean this collection is also a social graph. Here are some resoures which may be helpful to you when thinking about schema design in MongoDB.

So now join is possible in mongodb and you can achieve this using $lookup and $facet aggregation here and which is probably the best way to find in multiple collections

db.collection.aggregate([
  { "$limit": 1 },
  { "$facet": {
    "c1": [
      { "$lookup": {
        "from": Users.collection.name,
        "pipeline": [
          { "$match": { "first_name": "your_search_data" } }
        ],
        "as": "collection1"
      }}
    ],
    "c2": [
      { "$lookup": {
        "from": State.collection.name,
        "pipeline": [
          { "$match": { "name": "your_search_data" } }
        ],
        "as": "collection2"
      }}
    ],
    "c3": [
      { "$lookup": {
        "from": State.collection.name,
        "pipeline": [
          { "$match": { "name": "your_search_data" } }
        ],
        "as": "collection3"
      }}
    ]
  }},
  { "$project": {
    "data": {
      "$concatArrays": [ "$c1", "$c2", "$c3" ]
    }
  }},
  { "$unwind": "$data" },
  { "$replaceRoot": { "newRoot": "$data" } }
])