Data Lake Storage Roadmap

by
Andrew Snodgrass

by
Andrew Snodgrass

Andrew analyzes and writes about Microsoft's data management, business intelligence, and machine learning solutions, as well as aspects of licensing... more

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

Recent Updates and Near-Term Roadmap (2025–2026)

ADLS is a mature offering that continues being improved by Microsoft, but at a much slower pace than in the past. The most notable updates for ADLS in 2025 include the following two items:

Azure Storage Actions is a new Azure resource that can help automate data management options across multiple storage accounts through the creation of operation-specific rules. Much like existing Lifecycle Management features for managing storage tiers, Storage Actions uses rules to perform a wide set of operations based on triggers, such as delete state, version, length, tags, and others. It can also be used to combine multiple conditions and perform multiple operations on a single trigger to address complex situations. Tasks can be assigned to multiple storage accounts to ensure consistent application of a rule and set to run on a predefined schedule.