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Deploy a Data Lake for an HTTP Data Store

On this page

  • Prerequisites
  • Procedure

This page describes how to deploy a Data Lake for accessing data in an HTTP data store.


The support for HTTP data stores is available as a Beta feature. The feature and the corresponding documentation may change at any time during the Beta stage.

Before you begin, you will need to:

  • Create a MongoDB Atlas account, if you do not have one already.
  • Format your data store using one of the supported data formats.


    If your file format is CSV or TSV, you must include a header row in your data. See Comma-Separated and Tab-Separated Value Data Files for more information.

  • Make your data store accessible over the public internet.
  • If your HTTP data store is not accessible over HTTPS, you must use the JSON Editor to configure your data store. In your JSON configuration, you must set the stores.[n].allowInsecure setting to true.
  • Atlas Data Lake does not support HTTP data store URLs that require authentication.
  • For your first Data Lake, click Create a Data Lake.
  • For your subsequent Data Lakes, click Configure a New Data Lake.
  • For a guided experience, click Visual Editor.
  • To edit the raw JSON, click JSON Editor.
  1. (Optional) Click the for the:

    • Data Lake to specify a name for your Data Lake. Defaults to Data Lake[n].
    • Database to edit the database name. Defaults to Database[n].

      Corresponds to databases.[n].name JSON configuration setting.

    • Collection to edit the collection name. Defaults to Collection[n].

      Corresponds to databases.[n] JSON configuration setting.

    • View to edit the view name.

    You can click:

    • Create Database to add databases and collections.
    • associated with the database to add collections to the database.
    • associated with the collection to add views on the collection. To create a view, you must specify:

      • The name of the view.
      • The pipeline to apply to the view.


        The view definition pipeline cannot include the $out or the $merge stage. If the view definition includes nested pipeline stages such as $lookup or $facet, this restriction applies to those nested pipelines as well.

      To learn more about views, see:

    • associated with the database, collection, or view to remove it.
  2. Drag and drop the data store to map with the collection.

    Corresponds to databases.[n].collections.[n].dataSources JSON configuration setting.

←  Deploy a Data Lake for an Atlas Cluster Data StoreConfiguring Data Lake →
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