Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

The Azure Data Lake connector will crawl content from a source such as Azure SQL Server on virtual machines, Azure SQL Database, and Azure SQL Data Warehouse. the Azure Data Lake Store cloud at either root or specified paths.

An Azure Data Lake makes it easy for developers, data scientists, and analysts to store data of any size, shape, and speed, for all types of processing and analytics across platforms. It removes the complexities of ingesting and storing data while making it faster to get up and running with batch, streaming, and interactive analytics. Azure Data Lake works with existing. It integrates seamlessly with operational stores and data warehouses so you can extend current data applications. 

For more information about the Azure Data Lake Store, see the official Microsoft Overview of Azure Data Lake Store documentation.


Panel
titleOn this page

Table of Contents

Features


Some of the features of the Azure Data Lake connector include:

  • Performs incremental crawling (so that only new/updated documents are indexed)
  • Fetches Object ACLs (Access Control Lists) for Azure document-level security
  • Runs from any machine with access to the given Data Lake source
  • Service-to-Service Authentication via OAuth 2.0 tokenExample Feature


Content Retrieved


The Azure Data Lake connector retrieves several types of documentsany type of document and its attributes. Listed below are the inclusions and exclusions of these included documents.

Include

  • Example Doc Type

Exclude

  • Example Doc Type

Limitations 

Due to API limitations, Azure Data Lake connector has the following limitations:

  • Example limitation
    • Example Reason
  • Documents stored in folders
  • Documents stored in subfolders


Future Development Plan


The following features are not currently implemented, but are on No new features have been identified to add to the development plan:

Example future plan

.

Anything we should add? Please let us know.