Time Series Data

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Overview

Create a Time Series Collection
Store Time Series Data
Query Time Series Data
Additional Information

Overview

In this guide, you can learn how to use the Scala driver to store and interact with time series data.

Time series data is composed of the following components:

Measured quantity
Timestamp for the measurement
Metadata that describes the measurement

The following table describes sample situations for which you could store time series data:

Situation	Measured Quantity	Metadata
Recording monthly sales by industry	Revenue in USD	Company, country
Tracking weather changes	Precipitation level	Location, sensor type
Recording fluctuations in housing prices	Monthly rent price	Location, currency

Create a Time Series Collection

Important

Server Version for Time Series Collections

To create and interact with time series collections, you must be connected to a deployment running MongoDB Server 5.0 or later.

You can create a time series collection to store time series data. To create a time series collection, pass the following parameters to the createCollection() method:

Name of the new collection to create
CreateCollectionOptions object with the TimeSeriesOptions set using the timeSeriesOptions() method

Example

This example creates the october2024 time series collection in the fall_weather database with the timeField option set to the "timestamp" field and the metaField option set to the "location" field:

val database = mongoClient.getDatabase("fall_weather")
val tsOptions = TimeSeriesOptions("timestamp").metaField("location")
val collectionOptions = CreateCollectionOptions().timeSeriesOptions(tsOptions)
val createObservable = database.createCollection("october2024", collectionOptions)
Await.result(createObservable.toFuture(), Duration(10, TimeUnit.SECONDS))

To verify that you successfully created the time series collection, run the listCollections() method on the database and print the results:

val listObservable = database.listCollections()
val list = Await.result(listObservable.toFuture(), Duration(10, TimeUnit.SECONDS))
val jsonSettings = JsonWriterSettings.builder().indent(true).build()
list.foreach(collection => {
  println(collection.toJson(jsonSettings))
})

{
  "name": "october2024",
  "type": "timeseries",
  "options": {
    "timeseries": {
      "timeField": "temperature",
      "granularity": "seconds",
      "bucketMaxSpanSeconds": 3600
    }
  },
  "info": {
    "readOnly": false
  }
}
...

Store Time Series Data

You can insert data into a time series collection by using the insertOne() or insertMany() methods and specifying the measurement, timestamp, and metadata in each inserted document.

Tip

To learn more about inserting documents into a collection, see the Insert Documents guide.

Example

This example inserts New York City temperature data into the october2024 time series collection created in the Create a Time Series Collection example. Each document contains the following fields:

temperature, which stores temperature measurements in degrees Fahrenheit
location, which stores location metadata
timestamp, which stores the time of the measurement collection

val collection = database.getCollection("october2024")
val temperatures = Seq(
  Document("timestamp" -> BsonDateTime(1727755200000L), "temperature" -> 54, "location" -> "New York City"),
  Document("timestamp" -> BsonDateTime(1727841600000L), "temperature" -> 55, "location" -> "New York City"),
)
val insertObservable = collection.insertMany(temperatures)
Await.result(insertObservable.toFuture(), Duration(10, TimeUnit.SECONDS))

Query Time Series Data

You can use the same syntax and conventions to query data stored in a time series collection as you use when performing read or aggregation operations on other collections. To learn more about these operations, see the Additional Information section.

Additional Information

To learn more about the concepts mentioned in this guide, see the following MongoDB Server manual entries:

To learn more about performing read operations, see Read Data from MongoDB.

To learn more about performing aggregation operations, see the Transform Your Data with Aggregation guide.

API Documentation

To learn more about the methods mentioned in this guide, see the following API documentation:

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