Overview
This node enables interaction with a MongoDB database, allowing users to perform various operations such as aggregation, querying, inserting, updating, and deleting documents within specified collections. The "Aggregate" operation specifically executes a MongoDB aggregation pipeline query, which is a powerful framework for data aggregation modeled on the concept of data processing pipelines.
Common scenarios where this node is beneficial include:
- Performing complex data transformations and computations on MongoDB collections.
- Filtering, grouping, and reshaping data before further processing in an n8n workflow.
- Generating reports or analytics by aggregating data directly within MongoDB.
Practical example: You might use the Aggregate operation to filter orders placed after a certain date, group them by customer, and calculate total sales per customer, all within a single aggregation pipeline.
Properties
| Name | Meaning |
|---|---|
| Collection | The name of the MongoDB collection on which the aggregation pipeline will be executed. |
| Query | The MongoDB aggregation pipeline expressed as a JSON array. This defines the sequence of stages to process the data (e.g., $match, $group, $sort). |
Output
The output consists of an array of items, each containing a json field representing a document resulting from the aggregation pipeline. Each document corresponds to one aggregated result from the MongoDB collection.
Example output item structure:
{
"json": {
// Aggregated document fields as returned by MongoDB
}
}
No binary data output is produced by this operation.
Dependencies
- Requires a MongoDB database accessible via connection string or credentials.
- Needs an API key credential or equivalent authentication configured in n8n to connect securely to the MongoDB instance.
- Uses the official MongoDB Node.js driver internally to execute queries.
Troubleshooting
- Invalid JSON in Query: If the aggregation pipeline JSON is malformed, the node will throw a parsing error. Ensure the JSON syntax is correct and properly formatted.
- Invalid ObjectId Format: If the pipeline references
_idfields as strings, they are automatically converted to ObjectId instances. However, invalid ObjectId strings will cause errors. - Database or Collection Not Found: Errors occur if the specified database or collection does not exist or is inaccessible. Verify the connection credentials and collection names.
- Permission Issues: Insufficient permissions on the MongoDB user may lead to authorization errors when running aggregation pipelines.
- Continue On Fail: If enabled, the node will continue processing other items even if some fail, returning error messages in the output instead of stopping execution.