Azure Stream Analytics vs Materialize

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

Materialize is a live data layer for apps and AI agents that uses SQL to create up-to-the-second views. Rather than rebuilding query results from scratch as data arrives, it updates them incrementally. Connected sources appear as continually updating tables with sub-second freshness. SQL features include multi-way, lateral, and outer joins, recursive SQL, and SUBSCRIBE, which streams query-result changes over a standard Postgres connection.

Materialize is wire-compatible with PostgreSQL and supports clients and tools that work with PostgreSQL. Listed integrations include PostgreSQL, MySQL, SQL Server, CockroachDB, Kafka, Model Context Protocol, dbt, and webhooks such as EventBridge and Segment. Transformed updates can go to downstream systems including Kafka and Apache Iceberg. It is available as managed Cloud, self-managed Kubernetes software, and a Docker-based local development Emulator. The free self-managed Community Edition is limited to 24 GiB memory and 48 GiB disk. Cloud On-Demand is $1.50 a month, with usage-based compute, storage, and networking; Cloud Capacity is $1.50 a year, with storage and networking billed separately.