Micronaut Framework VS Apache Flink

Micronaut has a share of the space too. https://micronaut.io/ However, you’re right that Spring Boot has the lions share of the Java ecosystem. - Source: Hacker News / 3 months ago

I've used vert.x in a big project once. I don't ever want to do that again. Performance is pretty good, but the developer experience is beyond clunky. My current favourite Java server framework is Micronaut. Great performance and easy to develop for! https://micronaut.io/. - Source: Hacker News / 3 months ago

One of the most common web frameworks used is Spring Boot - here is their quickstart: https://spring.io/quickstart Newer alternatives are: https://micronaut.io/ and https://quarkus.io/ If you want to have something really simple look at Javalin: https://javalin.io/. - Source: Hacker News / 8 months ago

I wonder how much you'd save with Micronaut: https://micronaut.io/ > Micronaut is a software framework for the Java virtual machine platform. It is designed to avoid reflection, thus reducing memory consumption and improving start times. Features which would typically be implemented at run-time are instead pre-computed at compile time. https://en.wikipedia.org/wiki/Micronaut_(framework) I don't think you'd go down... - Source: Hacker News / 10 months ago

I'd like to introduce my project. It is called mlfx. It can compile FXML ahead of time. It is basically an annotation processor, which internally uses Micronaut framework's AST abstraction and compiles fxml files directly to JVM bytecode. This decreases UI load time and also helps with native-image reflection configs. It also has some compliance tests that load compiled code and Check resulting object graph... Source: 12 months ago

You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / 5 days ago

Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / about 1 month ago

Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago

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. - Source: dev.to / 5 months ago

Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago