Based on our record, Akka should be more popular than Apache Storm. It has been mentiond 21 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Kotlin also has a construct for asynchronous collections/streams. Kotlin's version of AsyncSequence is called a Flow. Just as Swift's AsyncSequence builds upon prior experience with RxSwift and Combine, Kotlin's Flow APIs build upon earlier stream/collection APIs in the JVM ecosystem: Java's RxJava, Java8 Streams, Project Reactor, and Scala's Akka. - Source: dev.to / 7 months ago
First-class distributed and multicore computing. Swift has first-class “actors” and “distributed” methods. Unison, Erlang, and Elixir are built with distributed being one of the #1 concerns. Though first-class is not super common and I don't really expect it to be because usually libraries are enough (e.g. Scala has Akka and is used WIDELY for distributed); whereas something like linear types and typed effects,... Source: about 1 year ago
Akka is a library that implements the actor model for JVM languages. Mainly in Scala, but you can use it in Java too, and maybe others. It doesn't feel as ergonomic as Elixir, but if Elixir is too "out there" for the decision makers in your case, this might be a friendlier alternative. Source: about 1 year ago
Kalix builds on the lessons we have learned from more than a decade of building Akka (leveraging the actor model) and our experience helping large (and small) enterprises move to the cloud and use it in the most time, cost, and resource-efficient way possible. - Source: dev.to / over 1 year ago
Note Akka, the Java & friends framework, is working with the actor model and have as main inspiration Erlang to mimic some features of the BEAM on top of the JVM. - Source: dev.to / over 1 year ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 1 year ago
Storm, a system for real-time and stream processing. - Source: dev.to / over 1 year ago
Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 1 year ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 2 years ago
Dapr - Application and Data, Build, Test, Deploy, and Microservices Tools
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Netty - Cloud-based real estate management solution
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
RxJS - Reactive Extensions for Javascript
Google BigQuery - A fully managed data warehouse for large-scale data analytics.