vert.x VS Apache Flink

vert.x Reviews

Apache Flink Reviews

vert.x mentions (26)

• Spark – A web micro framework for Java and Kotlin

  Https://vertx.io/ It's actively maintained with full time developers, performant, supports Kotlin out of the box, and has more features? - Source: Hacker News / 2 months ago

• Reactive database access on the JVM

  Hibernate Reactive integrates with Vert.x, but an extension allows to bridge to Project Reactor if wanted. - Source: dev.to / 10 months ago

• What's the state of server-side frameworks with Kotlin support today for small teams?

  Personally, I like vertx, it is modular and you can pick and choose what you need. It also has support for kotlin coroutines, https://vertx.io/, https://github.com/vert-x3/vertx-examples/tree/4.x/kotlin-examples. Source: about 1 year ago

• Anything close beam/otp for other languages?

  I really like Eclipse Vert.x... As both an Erlang dev and Java dev, it's a great synergy and soon to have support for Virtual Threads similar to BEAM. Source: about 1 year ago

• Favorite hidden gem library?

  Eclipse Vert.x - Add amazing Async to any Java stack. Source: over 1 year ago

Apache Flink mentions (27)

• Top 10 Common Data Engineers and Scientists Pain Points in 2024

  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 / 14 days ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  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 / 2 months ago

• Go concurrency simplified. Part 4: Post office as a data pipeline

  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 / 4 months ago

• Five Apache projects you probably didn't know about

  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 / 4 months ago

• Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog

  Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 4 months ago