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Akka

807
843
+ 1
85
Erlang

754
655
+ 1
314
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Akka vs Erlang: What are the differences?

Akka: Build powerful concurrent & distributed applications more easily. Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM; Erlang: A programming language used to build massively scalable soft real-time systems with requirements on high availability. Some of Erlang's uses are in telecoms, banking, e-commerce, computer telephony and instant messaging. Erlang's runtime system has built-in support for concurrency, distribution and fault tolerance. OTP is set of Erlang libraries and design principles providing middle-ware to develop these systems.

Akka and Erlang are primarily classified as "Concurrency Frameworks" and "Languages" tools respectively.

"Great concurrency model" is the primary reason why developers consider Akka over the competitors, whereas "Real time, distributed applications" was stated as the key factor in picking Erlang.

Akka and Erlang are both open source tools. Akka with 10.1K GitHub stars and 3.04K forks on GitHub appears to be more popular than Erlang with 7.75K GitHub stars and 2.1K GitHub forks.

According to the StackShare community, Akka has a broader approval, being mentioned in 76 company stacks & 57 developers stacks; compared to Erlang, which is listed in 70 company stacks and 47 developer stacks.

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Pros of Akka
Pros of Erlang
  • 31
    Great concurrency model
  • 16
    Fast
  • 11
    Actor Library
  • 10
    Open source
  • 7
    Resilient
  • 5
    Scalable
  • 5
    Message driven
  • 59
    Concurrency Support
  • 59
    Real time, distributed applications
  • 55
    Fault tolerance
  • 34
    Soft real-time
  • 30
    Open source
  • 20
    Functional programming
  • 19
    Message passing
  • 14
    Immutable data
  • 12
    Works as expected
  • 4
    Facebook chat uses it at backend
  • 3
    Practical
  • 3
    Knowledgeable community
  • 2
    Bullets included

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Cons of Akka
Cons of Erlang
  • 3
    Mixing futures with Akka tell is difficult
  • 2
    Closing of futures
  • 2
    No type safety
  • 1
    Typed actors still not stable
  • 0
    Very difficult to refactor
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    What is Akka?

    Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM.

    What is Erlang?

    Some of Erlang's uses are in telecoms, banking, e-commerce, computer telephony and instant messaging. Erlang's runtime system has built-in support for concurrency, distribution and fault tolerance. OTP is set of Erlang libraries and design principles providing middle-ware to develop these systems.

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    What companies use Akka?
    What companies use Erlang?
    See which teams inside your own company are using Akka or Erlang.
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    What tools integrate with Akka?
    What tools integrate with Erlang?

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    What are some alternatives to Akka and Erlang?
    Spring
    A key element of Spring is infrastructural support at the application level: Spring focuses on the "plumbing" of enterprise applications so that teams can focus on application-level business logic, without unnecessary ties to specific deployment environments.
    Scala
    Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.
    Kafka
    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
    Spring Boot
    Spring Boot makes it easy to create stand-alone, production-grade Spring based Applications that you can "just run". We take an opinionated view of the Spring platform and third-party libraries so you can get started with minimum fuss. Most Spring Boot applications need very little Spring configuration.
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    See all alternatives