Azure Data Lake Store (ADLS) is a fully managed, elastic, scalable, and secure file system that supports semantics of the Hadoop distributed file system (HDFS) and the Microsoft Cosmos file system. It is specifically designed and optimized for a broad spectrum of big data analytics that depend on an extremely high degree of parallel reads and writes, as well as colocation of compute and data for high-bandwidth and low-latency access. It brings together key components and features of Cosmos — long used internally at Microsoft as the warehouse for data and analytics — and HDFS. It also is a unified file storage solution for analytics on Azure. Internal and external workloads run on this unified platform. Distinguishing aspects of ADLS include its support for multiple storage tiers, exabyte scale, and comprehensive security and data sharing. Raghu Ramakrishnan will cover ADLS architecture, design points, the Cosmos experience, and performance.