MongoDB Atlas Data Lake, Overview and Use-case Demonstration

PublishedJune 10, 2020

MongoDB is excited to bring our flexible data model and expressive query language to your data wherever it lives today. We have always supported using data in a way that makes the most sense for a user's workflow and application. We are now bringing that level of convenience to data lakes. With the Atlas Data Lake we are giving customers the ability to interact with rich data using the language best suited for the task: MQL. We are expanding the footprint of our Aggregation Pipeline, which already powers flexible data pipelines on operational data, to query large corpora of offline data. Lastly, we are changing the nature of data lakes as we expand the number of supported underlying sources, allowing you to deliver insights without moving or transforming your data. Learn how Atlas Data Lake can help you eliminate the cost and complexity of data movement, reduce the effort of managing schema, and decrease the time to insight.