Azure Stream Analytics vs Confluent Cloud

Azure Stream Analytics has no write-up on Specifiction yet; its figures are above.

Confluent Cloud is a managed data streaming platform built on a serverless Apache Kafka engine. It is designed for real-time streaming, event-driven applications, analytics, and AI/ML workloads. Cluster choices include Basic, Standard, Enterprise, and Freight, as well as Dedicated clusters with pre-provisioned resources. Confluent says its cloud-native engine adjusts cluster infrastructure to workload needs. Cluster Linking replicates, synchronizes, and shares data across regions, public clouds, and organizations. The service includes managed Kafka connectors for databases, data lakes, and warehouses, serverless processing with Apache Flink, and a managed Stream Governance suite. Tableflow can materialize Kafka topics and schemas as Apache Iceberg and Delta Lake tables. Listed security features include RBAC, self-managed encryption keys, client-side field-level encryption, and audit logs. Users can manage clusters and topics through a web UI or CLI; supported client languages include Java, Python, .NET, Go, Node.js, and C/C++. It is available on AWS, Azure, and Google Cloud across more than 100 regions. A free plan is available; paid plans start at $385/mo, and new signups receive a 30-day trial.