High-Performance Hosted Hadoop at Massive Scale

Azure Data Lake is a scalable managed Hadoop storage service that can ingest and process large amounts of unstructured data in their native formats at high rates. Compared to Azure HDInsight, Microsoft’s existing Hadoop service, Data Lake provides better query performance and access without file and account size limitations. The service will be a viable alternative to on-premises Hadoop deployments, especially for organizations that want to test Big Data analytics without substantial hardware investment. Data Lake is currently in private preview with a public preview expected in late 2015.

Finding Value in Big Data

A “data lake” is a storage repository (frequently based on Hadoop) whose purpose is to hold vast amounts of unprocessed data (often called Big Data) in its native format until it is needed. For example, data lakes are used to store Web server logs, streaming sensor data, and social media posts. The data are typically unstructured, and the content and format change unpredictably over time, which makes analyzing the data with traditional, structured database solutions complex.