MongoDB Atlas Data Lake Debuts at MongoDB World | MongoDB Blog` The new member of the MongoDB Atlas family, MongoDB Atlas Data Lake, is a cloud-based data lake service that enables users to process and analyze large amounts of data in JSON, BSON, CSV, TSV, Avro, and Parquet formats. With MongoDB Atlas Data Lake, users can work with their data faster by not having to define a schema beforehand, and they can leverage the MongoDB Query Language to analyze their data on demand without infrastructure setup or time-consuming transformations. The service is designed to be compatible with existing tools and platforms, including MongoDB drivers, the MongoDB Shell, and Jupyter Notebooks, allowing users to apply one skill set to both their transactional databases and data lakes. The service uses a distributed architecture that deploys multiple compute nodes in parallel to analyze each S3 bucket and process queries against its data, providing fast processing and minimizing data transfer costs. As an on-demand service available in the MongoDB Atlas cloud data platform, users can configure Atlas Data Lake from the same UI as operational clusters using a simple wizard, and they will receive stats on queries executed, data scanned, and returned, as well as average execution time.