I’m currently working on a mongoDB collection containing documents that looks like the following :

{ startTime : Date, endTime: Date, source: String, metaData: {}}

And my usecase is to retrieve all documents that is included within a queried time frame, such as my query looks like this :

db.myCollection.find(
    {
        $and: [
            {"source": aSource},
            {"startTime" : {$lte: timeFrame.end}},
            {"endTime" : {$gte: timeFrame.start}}
        ]
    }
).sort({ "startTime" : 1 })

With an index defined as the following :

    db.myCollection.createIndex( { "source" : 1, "startTime": 1, "endTime": 1 } );

The problem is that queries are very slow (multiple hundreds of ms on a local database) as soon as the number of document per source increase.

Using mongo explain shows me that i’m efficiently using this index (only found documents are scanned, otherwise only index-access is made), so the slowness seems to come from the index scan itself, as this query needs to go over a large portion of this index.

In addition to that, such an index gets huge pretty quickly and therefore seems inefficient.

Is there anything i’m missing that could help makes those queries faster, or am I condemned to retrieve all the documents belonging to a given source as the best way to go ? I see that mongo now provides some time-series features, could that bring any help in regard of my problem ?