A real-time analytics database called Apache Druid is developed for quick slice-and-dice analysis on massive data volumes. The best data for Apache Druid is event-oriented and frequently utilized as the database backend for analytical application GUIs and for highly concurrent APIs that require quick aggregations. Druid can be leveraged very effectively, where real-time ingestion, fast query performance, and high uptime are crucial.
At the other end, Apache Kafka is gaining outstanding momentum as a distributed event streaming platform with excellent performance, low latency, fault tolerance, and high throughput and having capable of handling thousands of messages per second.