memphis VS ApacheKafka

Hey check out the first good issues in the Memphis.dev open source

Try Memphis.dev blog or you can check out Github

- https://github.com/memphisdev/memphis

Argo is a collection of open-source tools for Kubernetes to run workflows, manage clusters, and do GitOps easily. Memphis is an open-source next-generation alternative to traditional message brokers.

I have dealt with the same problem. It depends what are the cycle intervals. If for example, it's every few minutes maybe it's worth keeping a machine on the cloud and the DB on that machine. in my opinion, it's a little bit expensive. The thing that worked for me is to run once a day a lambda function and store the data on a message broker. You should take a look at memphis.dev which is open-source and very easy to work with.

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Join our 2K stargazers on Github and try Memphis out, I am sure you are going to be surprised 📷 https://github.com/memphisdev/memphis-broker

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.