Mongoose: how to use aggregate and find together

For MongoDB 3.6 and greater, use the $expr operator which allows the use of aggregation expressions within the query language:

var followers_count = 30;
db.locations.find({
   "$expr": { 
       "$and": [
           { "$eq": ["$name", "development"] },
           { "$gte": [{ "$size": "$followers" }, followers_count ]}
       ]
    }
});

For non-compatible versions, you can use both the $match and $redact pipelines to query your collection. For example, if you want to query the locations collection where the name is ‘development’ and followers_count is greater than 30, run the following aggregate operation:

const followers_count = 30;
Locations.aggregate([
    { "$match": { "name": "development" } },
    {
        "$redact": {
            "$cond": [
                { "$gte": [ { "$size": "$followers" }, followers_count ] },
                "$$KEEP",
                "$$PRUNE"
            ]
        }
    }
]).exec((err, locations) => {
    if (err) throw err;
    console.log(locations);
})

or within a single pipeline as

Locations.aggregate([
    {
        "$redact": {
            "$cond": [
                { 
                    "$and": [
                        { "$eq": ["$name", "development"] },
                        { "$gte": [ { "$size": "$followers" }, followers_count ] }
                     ]
                },
                "$$KEEP",
                "$$PRUNE"
            ]
        }
    }
]).exec((err, locations) => {
    if (err) throw err;
    console.log(locations);
})

The above will return the locations with just the _id references from the users. To return the users documents as means to “populate” the followers array, you can then append the $lookup pipeline.

If the underlying Mongo server version is 3.4 and newer, you can run the pipeline as

let followers_count = 30;
Locations.aggregate([
    { "$match": { "name": "development" } },
    {
        "$redact": {
            "$cond": [
                { "$gte": [ { "$size": "$followers" }, followers_count ] },
                "$$KEEP",
                "$$PRUNE"
            ]
        }
    },
    {
        "$lookup": {
            "from": "users",
            "localField": "followers",
            "foreignField": "_id",
            "as": "followers"
        }
    }
]).exec((err, locations) => {
    if (err) throw err;
    console.log(locations);
})

else you would need to $unwind the followers array before applying $lookup and then regroup with $group pipeline after that:

let followers_count = 30;
Locations.aggregate([
    { "$match": { "name": "development" } },
    {
        "$redact": {
            "$cond": [
                { "$gte": [ { "$size": "$followers" }, followers_count ] },
                "$$KEEP",
                "$$PRUNE"
            ]
        }
    },
    { "$unwind": "$followers" },
    {
        "$lookup": {
            "from": "users",
            "localField": "followers",
            "foreignField": "_id",
            "as": "follower"
        }
    },
    { "$unwind": "$follower" },
    {
        "$group": {
            "_id": "$_id",
            "created": { "$first": "$created" },
            "name": { "$first": "$name" },
            "followers": { "$push": "$follower" }
        }
    }
]).exec((err, locations) => {
    if (err) throw err;
    console.log(locations);
})