The new native MongoDB Connector for Apache Spark offers higher performance, greater ease of use, and access to more advanced Spark functionality than any existing connector. This allows users to operationalize results generated from Spark within real-time business processes supported by MongoDB, enabling organizations to unlock valuable insights from their data quickly and act on them in real-time. The new connector is designed for developers and data scientists building modern applications incorporating sophisticated real-time analytics, and provides a more natural development experience as it's written in Spark's native language. It also offers support for advanced Spark features such as DataFrames, Datasets, Machine Learning, GraphX, Streaming, and SQL APIs, as well as data locality awareness and MongoDB secondary indexes to filter input data. The new connector is now available for early access evaluation and can be integrated with a variety of storage and messaging platforms including Amazon S3, Kafka, HDFS, relational databases, NoSQL datastores, and more.