Data Lake Storage Roadmap

Azure Data Lake Storage (ADLS) provides general data lake storage features to capture and analyze various data types. Data lakes typically store vast amounts of unprocessed data in its native format; for example, a data lake might perform high-speed ingestion of logs and sensor data. On-premises data lakes can be expensive and are difficult to scale and manage. ADLS simplifies some of the complexities by providing petabyte-level storage and high-performance computing as a managed cloud service. ADLS is used by various Azure-based analytics services, such as Fabric, and the data it stores can be queried programmatically and with third-party tools.

Product: Data Lake Storage

Near Term (2024–2025)

The most notable change to ADLS is the introduction of OneLake, the core data storage component in Microsoft Fabric, a new data and analytics offering. OneLake is a data management layer that sits on top of ADLS, automatically deploying ADLS storage accounts and controlling access to data through Fabric workspaces. OneLake presents Fabric users with a single virtual storage account that can accept any kind of data and reduces the need to copy data between workloads. OneLake is not a threat to ADLS, but rather strengthens Microsoft’s commitment to the underlying ADLS service.