Documentation Plugins MongoDB data source Query editor

MongoDB query editor

Grafana provides a query editor for MongoDB that supports the same syntax as the MongoDB Shell (mongosh), with the following limitations:

• Only one command can be executed per query panel.
• Only find and aggregate read commands are supported.
• Supported date constructors include ISODate, new Date, Date, and Date.now().

For an introduction to writing scripts for the MongoDB shell refer to Write scripts in MongoDB documentation. You create a query in the Grafana query editor in the same way you would in the MongoDB shell.

Example:

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sample_mflix.movies.aggregate([
            {"$match": { "year": {"$gt" : 2000} }},
            {"$group": { "_id": "$year", "count": { "$sum": 1 }}},
            {"$project": { "_id": 0, "count": 1, "time": { "$dateFromParts": {"year": "$_id", "month": 2}}}}
            ]
          ).sort({"time": 1})

Grafana Assistant

Starting with plugin version 1.27.0, the query editor includes a Grafana Assistant button that provides AI-assisted help with writing MongoDB queries. Click the Assistant button in the query editor toolbar to get suggestions and help constructing your queries.

Additional syntax

The editor extends the MongoDB Shell syntax with the following features.

Database selection

You can use a database name instead of db. For example, sample_mflix.movies.find(). You can still use db to refer to the default database in your connection string.

Aggregate sorting

Sorting typically happens within the aggregate pipeline. The extended syntax allows sorting on aggregate similarly to find. For example, sample_mflix.movies.aggregate({}).sort({"time": 1}).

Collections with a dot

To query collections that contain a dot (.) in their name, use the following syntax:

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my_db.getCollection("my.collection").find({})

Keyboard shortcuts

Press Ctrl+Space to show code completion, which is displayed after entering a . after a database, collection, query method, or aggregation method name. Pressing Cmd+S (macOS) or Ctrl+S (Windows/Linux) runs the query.

Query as time series

Create a time series query by aliasing the date field as time.

The following query converts the int field year to a date that is projected as time using the MongoDB $dateFromParts pipeline operator:

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sample_mflix.movies.aggregate([
{"$match": { "year": {"$gt" : 2000} }},
{"$group": { "_id": "$year", "count": { "$sum": 1 }}},
{"$project": { "_id": 0, "count": 1, "time": { "$dateFromParts": {"year": "$_id", "month": 2}}}}
]
).sort({"time": 1})

If you want to group your time series by Metric, project a field called __metric.

The following query displays the count of movies over time by movie rating using __metric:

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sample_mflix.movies.aggregate([
{"$match": { "year": {"$gt" : 2000}}},
{"$group": { "_id": {"year":"$year", "rated":"$rated"}, "count": { "$sum": 1 } }},
{"$project": { "_id": 0, "time": { "$dateFromParts": {"year": "$_id.year", "month": 2}}, "__metric": "$_id.rated", "count": 1}}
]
).sort({"time": 1})

Faceted queries

When $facet is the last stage in your aggregation pipeline, the plugin returns multiple named data frames – one for each facet group. This is useful when you want to display different aggregations of the same data in separate panels or table columns.

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sample_mflix.movies.aggregate([
  {
    "$facet": {
      "by_genre": [
        {"$group": {"_id": "$genres", "count": {"$sum": 1}}}
      ],
      "by_year": [
        {"$group": {"_id": "$year", "count": {"$sum": 1}}}
      ]
    }
  }
])

Date type detection

Append .detect() to a query to trigger automatic date-type detection for fields in the results. The backend probes the collection to identify which fields contain date values and converts them appropriately.

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sample_mflix.movies.find({"year": {"$gt": 2000}}).detect()

Diagnostics

MongoDB provides diagnostic commands to help monitor and troubleshoot database performance, health, and operations. For information about diagnostics commands, refer to Diagnostic Commands in MongoDB documentation.

The plugin supports the following MongoDB diagnostic commands:

• buildInfo
• connPoolStats
• connectionStatus
• dbStats
• getLog
• hostInfo
• lockInfo
• replSetGetStatus
• serverStatus
• stats

Macros

To simplify syntax and to allow for dynamic times, you can write queries that contain macros. The MongoDB plugin supports the following macros:

Example usage:

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sample_mflix.movies.find({ "tomatoes.dvd": { $gte: $__timeFrom, $lt: $__timeTo } })

Dynamic dates in queries

Starting with plugin version 1.14.2, performing arithmetic on dates directly within the query editor is no longer supported. In earlier versions of MongoDB (prior to version 5), date arithmetic was commonly used to filter documents.

Example of previously supported syntax (no longer works):

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sample_mflix.movies.find({"released": { $gte: new Date(new Date().setMonth(new Date().getMonth() - 3)) }})

With MongoDB version 5.0 and later, new operators such as $dateSubtract and $dateAdd were introduced. These operators provide more robust and flexible date manipulation, especially within aggregation queries.

The following example uses $dateSubtract to filter documents on the sample_mflix dataset:

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sample_mflix.movies.aggregate([
  {
    $match: {
      $expr: {
        $gt: [
          "$released",
          {
            $dateSubtract: {
              startDate: "$$NOW",
              unit: "year",
              amount: 9
            }
          }
        ]
      }
    }
  }
])

The query filters for movies released in the last 9 years using MongoDB native date manipulation features.