Apache Druid vs Azure Stream Analytics

Apache Druid is a free, open-source analytics database for querying streaming and batch data. It is designed to return OLAP queries in milliseconds, including on high-cardinality datasets with billions to trillions of rows. The project describes applications ranging from hundreds to 100,000 queries per second. Native Apache Kafka and Amazon Kinesis integrations support low-latency ingestion and querying as data arrives. Druid organizes ingested data into columnar, time-indexed, encoded and compressed storage. Queries can use Druid SQL or JSON-over-HTTP, and joins are available during ingestion or at query time. Its web console can load data, manage datasources and tasks, show server status and run queries. Extensions connect to storage, databases and formats including S3, HDFS, Azure, PostgreSQL, Avro, ORC and Parquet. Druid can be self-hosted on Linux, macOS and other Unix-like systems; Windows is not supported. The local quickstart needs at least 6 GiB of RAM and Java 17. Production security controls require configuration.

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