Haskell
Rust
JavaScript
Python
Java
Clojure
Elixir
NIM
Apache Storm
Apache Spark
Apache Flink
Qubole
Hadoop
Google BigQuery
Apache Kafka
Amazon Kinesis
We recommend LibHunt Haskell for discovery and comparisons of trending Haskell projects.
Haskell Apache StormBased on our record, Haskell 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.
Haskell - a general-purpose functional language with many unique properties (purely functional, lazy, expressive types, STM, etc). You mentioned you dabbled in Haskell, why not try it again? (I've written about 7 things I learned from Haskell, and my book is linked at them bottom if you're interested :) ). Source: about 3 years ago
Where you go is entirely up to you. According to haskell.org, Haskell jobs are a-plenty. sigh. Source: over 3 years ago
Should they be part of haskell.org or something else? Source: over 3 years ago
Haskell.org now has a big purple Get Started button that takes you to a nice short guide (haskell.org/get-started) that quickly provides all the basic info to get going with Haskell. It is aimed for beginners, to reduce choice fatigue and to give them a clear, official path to get going. Source: over 3 years ago
I just jumped into the wiki "Write Yourself a Scheme in 48 hours" which looks pretty good. (although some of the text explanation is hard to understand without context).. I used cabal to set up the starter project. Sublime editor seems to work OK and I just use the git Bash shell on windows to compile the program directly on the command line. So maybe this is all good enough for now (?). It seems installing... Source: over 3 years ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 3 years 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lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem.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 3 years ago
Storm, a system for real-time and stream processing. - Source: dev.to / over 3 years 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: almost 4 years 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 4 years ago
Rust - A safe, concurrent, practical language
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
