ApacheKafka VS redpanda

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.

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.

Yeah it’s just the stack switching itself that is a handful of cycles, but there is not much more overhead for the full VM switch if you structure your embedding the right way. Code the code is source available if you want to peek at it!

https://github.com/redpanda-data/redpanda/blob/dev/src/v/was...

that's a littlebit of a stretch. when you say "no shortage" - outside of redpanda what product exists that actually compete in all deployment modes?

it's a misconception that redpanda is simply a better kafka. the way to think about it is that is a new storage engine, from scratch, that speaks the kafka protocol. similar to all of the pgsql companies in a different space, i.e.: big table pgsql support is not a better postgres, fundamentally different tech. you can read the src and design here: https://github.com/redpanda-data/redpanda. or an electric car is not the same as a combustion engine, but only similar in that they are cars that take you from point a to point b.

Redpanda with the MongoDB Debezium Connector installed. We use Redpanda as a Kafka broker.

And Kafka + Kafka Connect has https://www.confluent.io/ https://aiven.io/ https://upstash.com/ (and not quite Kafka, but protocol-compatible, https://redpanda.com/)

There exists a C++ project which was created after Rust the language was available. github.com/redpanda-data/redpanda/

I suggest you check out io_uring and thread per core architecture. Applications like scylladb and redpanda have thread per core architecture and use io_uring for async io.

Redpanda