pippin VS ApacheKafka

take a look at the concurrent code written by other devs out there: for example, feel free to check the internals of my library Pippin, but I bet there are many better projects out there to learn from - Google/Bing/DuckDuckGo/Kagi and ChatGPT can help to find the right one

Christmas season is around the corner, that's why another evening I was standing in a long queue at the post office with some Xmas presents packed inside the box. The line moved pretty slowly, as there was only one postman for the whole crowd of customers. The guy was running back and forth, and I felt really sorry for him. Not sure why, either out of boredom or because of several long evenings I spent working on my open-source library for managing asynchronous pipelines, but my brain turned engineering mode on and tried to optimize the process of handling parcels.

Senden an Kafka (d. h. Senden der Daten an Apache Kafka)

Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a machine's temperature exceeds a certain threshold, a streaming platform can instantly trigger an alert and engineers do timely maintenance.

Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time.

*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...)

RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput.

Apache Kafka is a distributed streaming platform to share data between applications and services in real-time.

also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.