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The MongoDB connector lets Summation query collections as datasets. A connection targets one database, and each collection you select becomes a dataset available to Addison, reports, dashboards, and the modeler.

What you’ll need

  • A MongoDB Atlas cluster or self-managed MongoDB deployment reachable from Summation.
  • The database name and either a host or a MongoDB connection string.
  • If authentication is enabled, a database user that can read the selected collections and run listCollections. MongoDB’s built-in read role is a common starting point.
  • For Atlas, an IP access list entry that permits connections from Summation.
For MongoDB Atlas, enter only the SRV hostname, such as cluster0.abc123.mongodb.net. Do not include mongodb+srv:// in the Host field. Summation detects Atlas hostnames and uses SRV discovery automatically.

Form fields

These fields are available in the connection wizard.
Use TLS mode: disabled only for a trusted development network. It sends database traffic without TLS. Summation does not expose MongoDB’s insecure preferred mode because that mode skips certificate and hostname validation.

Connect to MongoDB Atlas

1

Allow network access

Add Summation’s egress addresses to the Atlas project’s IP access list.
2

Create a database user

Create a user with read access to the database and collections you want to expose.
3

Enter the SRV hostname

Copy the hostname from the Atlas connection string. For mongodb+srv://cluster0.abc123.mongodb.net/, enter cluster0.abc123.mongodb.net as Host. Keep TLS mode set to required.
4

Test and select collections

Click Test connection, then select the collections Summation should add as datasets.

Advanced configuration

The connector API accepts these additional configuration fields. They are not currently shown in the connection wizard.
mongodb_connection_string and mongodb_pass are secrets. Send them in the connector’s secrets payload, never in its non-secret config. Saved secret values are write-only and are not returned by the API.

Schema inference and nested documents

MongoDB collections can contain documents with different fields and types. Summation samples mongodb_num_docs_to_infer_schema documents to establish the dataset schema. Increase the sample count when fields are sparse or appear only in later documents. Larger samples improve coverage but make initial schema discovery slower. Enable Flatten nested objects to expose the first level of embedded documents as columns. For example, customer.region becomes a column while deeper objects remain JSON strings. Arrays remain array values rather than being expanded into multiple rows. Leave the setting off to keep embedded documents as JSON values.

Adding datasets

The connection wizard lists collections from the configured database. Source references use:
Collection names that require quoting use double quotes:
The wizard creates the correct source reference automatically.

Common problems