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Apache Kafka

Ecosystem

Kafka vs Traditional message System

Traditional Messaging System Kafka Streaming Platform
Transient message persistance Stores events based on a retention time. Events are immutable.
Brokers responsibility to keep track of consumed messages. Consumers responsiblity to keep track of consumed messages.
Target a specific Consumer. Any Consumer can access a message from the Broker.
Not a distributed system. Distributed streaming system.

Use Cases

  • To process payments and financial transactions in real-time, such as in stock exchanges, banks, and insurances.

  • To track and monitor cars, trucks, fleets, and shipments in real-time, such as in logistics and the automotive industry.

  • To continuously capture and analyze sensor data from IoT devices or other equipment, such as in factories and wind parks.

  • To collect and immediately react to customer interactions and orders, such as in retail, the hotel and travel industry, and mobile applications.

  • To monitor patients in hospital care and predict changes in condition to ensure timely treatment in emergencies.

  • To connect, store, and make available data produced by different divisions of a company.

  • To serve as the foundation for data platforms, event-driven architectures, and microservices.