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Time Series — MongoDB Manual

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Time series data is a sequence of data points in which insights are gained by analyzing changes over time. Time series data is generally composed of these components: Time when the data point was recorded. Metadata (sometimes referred to as source), which is a label or tag that uniquely identifies a series and rarely changes. Measurements (sometimes referred to as metrics or values), which are the data points tracked at increments in time. Generally these are key-value pairs that change over time. This table shows examples of time series data: For efficient time series data storage, MongoDB provides time series collections. New in version 5.0. You can use time series collections with deployments hosted in the following environments: MongoDB Atlas : The fully managed service for MongoDB deployments in the cloud MongoDB Enterprise: The subscription-based, self-managed version of MongoDB MongoDB Community: The source-available, free-to-use, and self-managed version of MongoDB To create a

Time Series - Database Manual - MongoDB Docs Docs Menu Ask MongoDB AI Docs Home / Development Docs Home / Development Docs Home / Development Time Series Copy page Time series data is a sequence of data points in which insights are gained by analyzing changes over time. Time series data is generally composed of these components: Time : Indicates when the data point was recorded. Metadata : A label or tag that identifies a data series and rarely changes. Metadata is stored in a metaField . You cannot add a metaField field to a time series document after you create it. Metadata is also known as

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