The correct answer is Azure HDInsight.

Azure HDInsight is a fully managed cloud service that provisions and runs distributed clusters for Hadoop and Spark and it supports other Hadoop ecosystem components such as HBase and Kafka. It is designed for large scale analytics pipelines and provides scalability, integration with Azure storage, and enterprise features like security and monitoring which make it suitable for running Hadoop and Spark workloads at scale.

Azure Databricks is a managed, optimized platform for Apache Spark that excels at interactive analytics and machine learning with collaborative notebooks and optimized runtimes, but the question calls for a distributed platform that explicitly runs the broader Hadoop ecosystem as well as Spark which makes HDInsight the better fit.

Azure Synapse Analytics provides an integrated analytics service with data warehousing and big data capabilities and it can run Spark pools, but it is focused on unified analytics and SQL data warehousing rather than being a dedicated managed Hadoop cluster service.

Azure Machine Learning is targeted at building, training, and deploying machine learning models and it is not a managed service for provisioning Hadoop clusters or for running general Hadoop ecosystem workloads.

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