Get started with Amazon DocumentDB

On the Amazon DocumentDB management console, under Clusters, choose Create.

On the Create Amazon DocumentDB cluster page, in the Cluster type section, choose Instance Based Clusters (this is the default option).

In the Configuration section:

1. For Cluster identifier, enter a unique name, such as mydocdbcluster. Note that the console will change all cluster names into lower-case regardless of how they are entered.

2. For Engine version, choose 5.0.0.

3. For Instance class, choose db.t3.medium. This is eligible for the AWS Free Tier.

4. For Number of instances, choose 1 instance. Choosing one instance helps minimize costs. If this were a production system, we would recommend that you provision three instances for high availability.

In the Cluster storage configuration section, choose Amazon DocumentDB Standard (this is the default option).

In the Connectivity section:

1. Select Connect to an EC2 compute resource.

2. For EC2 Instance, select the EC2 instance you created in Prerequisites.

In the Authentication section, enter sign-in credentials.

Leave all other options as default and choose Create cluster.

On the Amazon DocumentDB management console, under Clusters, locate your cluster. Choose the cluster you created by clicking on the cluster identifier.

Encryption-in-transit is enabled by default on Amazon DocumentDB. You can optionally disable TLS. To download the current certificate required to authenticate to your cluster, in the Connectivity & security tab, in the Connect section, under Download the Amazon DocumentDB Certificate Authority (CA) certificate required to authenticate to your cluster, copy the command provided. Go back to your Amazon EC2 instance and paste the command.

Return to your cluster in the Amazon DocumentDB console, under Connectivity & security tab, in the Connect section, under Connect to this cluster with the mongo shell, copy the connection string provided. Omit copying <insertYourPassword> so that you are prompted for the password by the mongo shell when you connect.

Go back to your Amazon EC2 instance and paste the connection string.

To insert a single document, enter the following:

db.collection.insert({"hello":"DocumentDB"})

You get the following output:

WriteResult({ "nInserted" : 1 })

You can read the document that you wrote with the findOne() command (because it only returns a single document). Input the following:

db.collection.findOne()

You get the following output:

{ "_id" : ObjectId("5e401fe56056fda7321fbd67"), "hello" : "DocumentDB"
                        }

To perform a few more queries, consider a gaming profiles use case. First, insert a few entries into a collection titled profiles. Input the following:

db.profiles.insertMany([
                    { "_id" : 1, "name" : "Matt", "status": "active", "level": 12, "score":202},
                    { "_id" : 2, "name" : "Frank", "status": "inactive", "level": 2, "score":9},
                    { "_id" : 3, "name" : "Karen", "status": "active", "level": 7, "score":87},
                    { "_id" : 4, "name" : "Katie", "status": "active", "level": 3, "score":27}
                    ])

You get the following output:

{ "acknowledged" : true, "insertedIds" : [ 1, 2, 3, 4 ] }

Use the find() command to return all the documents in the profiles collection. Input the following:

db.profiles.find()

You will get an output that will match the data you typed in Step 5.

Use a query for a single document using a filter. Input the following:

db.profiles.find({name: "Katie"})

You should get back this output:

{ "_id" : 4, "name" : "Katie", "status": "active", "level": 3,
                        "score":27}

Now let’s try to find a profile and modify it using the findAndModify command. We’ll give the user Matt an extra ten points with the following code:

db.profiles.findAndModify({
                query: { name: "Matt", status: "active"},
                update: { $inc: { score: 10 } }
            })

You get the following output (note that his score hasn’t increased yet):

{
        "_id" : 1,
        "name" : "Matt",
        "status" : "active",
        "level" : 12,
        "score" : 202
}

You can verify that his score has changed with the following query:

db.profiles.find({name: "Matt"})

You get the following output:

{ "_id" : 1, "name" : "Matt", "status" : "active", "level" : 12, "score"
                        : 212 }