Akka net vs

Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM. On the other hand, Orleans is detailed as " An approach to building distributed applications in.

NET ". Orleans is a framework that provides a straightforward approach to building distributed high-scale computing applications, without the need to learn and apply complex concurrency or other scaling patterns. It was created by Microsoft Research and designed for use in the cloud. Akka and Orleans can be categorized as "Concurrency Frameworks" tools.

Akka and Orleans are both open source tools. It seems that Akka with 9. Akka powers our asynchronous document upload processor, handling e. Akka Stacks. Orleans 24 Stacks. Need advice about which tool to choose? Ask the StackShare community!

Akka vs Orleans: What are the differences? What is Akka? What is Orleans? Why do developers choose Akka? Why do developers choose Orleans? Sign up to add, upvote and see more pros Make informed product decisions. What are the cons of using Akka? What are the cons of using Orleans? Be the first to leave a con.

Sign up to add, upvote and see more cons Make informed product decisions. What companies use Akka? What companies use Orleans? Delivery Hero SE. Odds Bods. Knowcross Solution Pvt Ltd. YunFan Inc. Nomnio d. Salad Technologies. Sign up to get full access to all the companies Make informed product decisions. What tools integrate with Akka? What tools integrate with Orleans?

No integrations found. What are some alternatives to Akka and Orleans? 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.

This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results.Discussion in ' Connected Games ' started by snacktimeSep 20, Search Unity. Log in Create a Unity ID. Unity Forum. Forums Quick Links.

Asset Store Spring Sale starts soon! Joined: Apr 15, Posts: 2, Thought this might be useful, since it includes information you won't know before you use both of them to some extent. I will be assuming that you know the basics of what these frameworks do. This is mainly for those that are actually evaluating which one to use and have done at least a basic level of research.

So preface, I am the author of Game Machine, which was one of the first frameworks to use the actor model for realtime game architectures. Since then most medium to large studios have adopted this architecture on new games. FYI Game Machine is dead, this isn't a plug. At the time creating it in.

Net simply wasn't an option, the tools weren't available. I've since moved on to using. Net, although have not released anything there as open source and it's likely I won't time considerations being why. So I have considerable experience and time testing java Akka. NET, and Orleans against similar workloads. In most cases the hot paths are basically the same code just ported to one of the 3 frameworks.

akka net vs

Ok so to the meat of it First a note on one of the most common problems faced with realtime games at any scale. Generally you want things local. Both to keep latencies lower and to avoid extra serialization cost. GC pressure from serialization becomes a real bottleneck, and one you can't solve by just throwing more memory or cpu at the problem. Most of the tests I did were against a common hotpath.

Messages that deal with position updates, the ones you are generally sending 20 times a second or so. MS Orleans Orleans has what they call the virtual actor model. In a nutshell the main difference is you can create an actor in a cluster with a unique id, and you don't have to care or know where it's at. It's all managed for you. This model is very nice, it fits most of what we do in realtime games.

So that's a big pro. The main con is that Orleans is slow in the single machine case. Calls to actors grains take around 10x longer and chew up considerably more cpu time then Akka. It's a very significant absolute difference. That said, it's not actually a huge deal in a lot of cases. You are trading the cost of extra hardware, for time and complexity you would face with another framework.

And for a small studio, that can be a really good trade off.A while back I created a thread on Twitter to attempt to explain the difference between Akka. What's the differences between these two pieces of technology? Can they be used together? Or are they competing technologies? The manner in which they distribute messages varies and for our purposes those differences are totally immaterial sorry, vendors.

The point is: producers write messages into these systems and the goal is, with varying degrees of reliability, concurrency, and asynchrony, to distribute these messages for processing to one or more downstream consumers.

Only in delivering and routing these messages from their sources and to their destinations. Where Akka. NET differs: Akka. NET actors are fundamentally message processing and message producing technologies. NET actors are responsible for managing business state or executing commands, both of which occur when an actor receives a message. Where the confusion occurs, however, is because Akka. You could, however, build a stand-alone system that runs entirely on Akka. NET and uses Akka.

Cluster to carry out all of the message distribution between different parts of the system AND all of the message production and processing needed to complete the work. There are some other differences between message distribution tools like Kafka and Akka.

NET that are worth noting:. This is because the vast majority of messages in Akka. Persistence to make delivery state durable and resilient to network failures. As of writing this, on. NET Framework 4. NET actor takes up about 1.

NET is very frequently used in combination with other messaging systems inside large-scale. NET applications. The most common reason is because Akka. NET simultaneously, like this one below:. In this scenario, the application compromises of multiple services that are developed by independent teams and have to carry out some sort of real-time workload on behalf of customers.

Akka.NET Bootcamp

Some high-level examples of this: real-time search, dynamic pricing, messaging, monitoring, and so on - some of the typical use cases for Akka. NET and Akka. The front-end application, an independent Akka.

NET cluster, might stream input from users to the back-end service, another real-time Akka. NET cluster performing state aggregation and reacting to changes in state.

In this scenario Kafka gets used as a layer for decoupling the two clusters from each other so one can be deployed without affecting the other - the business logic cluster consumes its data from the web UI cluster and produces updated outcomes in real-time, which in-turn might be consumed by other services not pictured on the diagram.Welcome to Akka.

NET, a set of open-source libraries for designing scalable, resilient systems that span processor cores and networks. Akka allows you to focus on meeting business needs instead of writing low-level code to provide reliable behavior, fault tolerance, and high performance. Common practices and programming models do not address important challenges inherent in designing systems for modern computer architectures.

To be successful, distributed systems must cope in an environment where components crash without responding, messages get lost without a trace on the wire, and network latency fluctuates.

These problems occur regularly in carefully managed intra-datacenter environments - even more so in virtualized architectures. All of these features are available through a uniform programming model: Akka. NET exploits the actor model to provide a level of abstraction that makes it easier to write correct concurrent, parallel and distributed systems.

The actor model spans the set of Akka. NET libraries, providing you with a consistent way of understanding and using them. Thus, Akka. NET offers a depth of integration that you cannot achieve by picking libraries to solve individual problems and trying to piece them together. By learning Akka. The characteristics of today's computing environments are vastly different from the ones in use when the programming models of yesterday were conceived.

Actors were invented decades ago by Carl Hewitt. But relatively recently, their applicability to the challenges of modern computing systems has been recognized and proved to be effective.

The actor model provides an abstraction that allows you to think about your code in terms of communication, not unlike people in a large organization.

The basic characteristic of actors is that they model the world as stateful entities communicating with each other by explicit message passing. What is Akka. To deal with these realities, Akka.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. Hi I'm in the early stage of choosing an actor framework for a project I'm about to start. As far as I know Orleans was meant to relief the developer of as much pain as possible, at cost of some performance.

In Akka. The only performance metrics I found around internet for Orleans are:. A grain will handle a maximum of 1, requests per second. A silo will handle a maximum of 10, requests per second. A silo will holdactive grains. I'd like to know what machines were used in the Akka. With the quotes from Orleans and Akka. I found this Akka. Orleans reports remote messages, see RPC.

That is a main difference. There are other differences as well of course. Besides the above, the only real advise I can give you is to measure yourself, for your realistic benchmark, in a setup that will be as close as possible to production in terms of communication pattern and number of servers. Learn more. Asked 3 years, 3 months ago.

Active 2 years ago. Viewed 8k times. And for Akka. Fritjof Berggren Fritjof Berggren 2, 1 1 gold badge 22 22 silver badges 41 41 bronze badges. I think you'll find that--as with all distributed computing--performance depends on a lot of factors, and your application logic is likely the primary one.

I prefer the Orleans approach because I'm a developer and I don't want to manage every detail, but that's just my opinion. Build prototypes using both approaches and see what works best.

What is Akka.NET?

As DanWilson already said, the benchmarks are based on a lot of factors so it is hard to really compare. While Akka.

NET is probably faster, it's also much lower-level. In terms of distributed computing, ease of scalability and development is often a lot more important than raw processing power.

I would by far prefer to save many developer-months of work at the cost of extra performance that I will never need anyway. Active Oldest Votes. BozoJoe 5, 3 3 gold badges 34 34 silver badges 59 59 bronze badges. Gabi Kliot Gabi Kliot 1, 4 4 silver badges 7 7 bronze badges. Sign up or log in Sign up using Google.I did however, feel I wanted to learn a bit more, so spent quite a few months experimenting with thing like.

Actors pop up in various frameworks such as:. This article will be about using Akka. NET which is a pretty complete port of the original Akkaso you will pretty much see how that works by the end of this too I hope. This is not the 1st time I have written about Actor models, in fact a while back I wrote quite a long post which is good background reading about an Actor model that I wrote for NetMQ the. You can read that post here:. I was very pleased but this actually made its way into the the actual NetMQ codebase, and is fully documented here:.

The Actor model adopts the philosophy that everything is an actor. This is similar to the everything is an object philosophy used by some object-oriented programming languages, but differs in that object-oriented software is typically executed sequentially, while the Actor model is inherently concurrent.

Decoupling the sender from communications sent was a fundamental advance of the Actor model enabling asynchronous communication and control structures as patterns of passing messages. Thus an actor can only communicate with actors whose addresses it has. It can obtain those from a message it receives, or if the address is for an actor it has itself created.

The Actor model is characterized by inherent concurrency of computation within and among actors, dynamic creation of actors, inclusion of actor addresses in messages, and interaction only through direct asynchronous message passing with no restriction on message arrival order. How I like to think of Actors is that they may be used to alleviate some of synchronization concerns of using shared data structures. The actor itself may pass messages to other actors, or work on the passed message itself.

By using message passing rather than using shared data structures, it may help to think of the actor or any subsequent actors its send messages to working on a copy of the data rather than working on the same shared structures. Which kind of gets rid of the need to worry about nasty things like lock s and any nasty timing issues that may arise from carrying out multi threaded code.

If the actor is working with its own copy of the data then we should have no issues with other threads wanting to work with the data the actor has, as the only place that data can be is within the actor itself, that is unless we pass another message to a different actor.

akka net vs

If we were to do that though the new message to the other actor would also be a copy of the data, so would also be thread safe. A fairly common thing to do is have multiple threads running to speed things up, but then you realise that your threads need to mutate the state of some shared data structure, so then you have to involve threading synchronization primitives most commonly lock. To take this one step further, lets see some code that may illustrate this further, imagine we had this sort of data structure representing a very slim bank account.

Nothing fancy there, just some fields. So lets now move onto looking at some threading code, I have chosen to just show two threads acting on a shared Account instance. I have possible picked an example that you think may not actually happen in real life, and to be honest this scenario may not popup in real life, as who would do something as silly as crediting an account in one thread, and debiting it in another…we are all diligent developers, we would not let this one into the code would we?

To be honest whether the actual example has real world merit or not, the point remains the same, since we have more than one thread accessing a shared data structure, access to it must be synchronized, which is typically done using a lock. The actor model, takes a different approach, where by message passing is used, which MAY involve some form of serialization as the messages are passed down the wire, which kind of guarantees no shared structures to contend with.

Well the rest of the article will be about how to develop code in.NET is a toolkit and runtime for building highly concurrent, distributed, and fault tolerant event-driven applications on. The Actor Model provides a higher level of abstraction for writing concurrent and distributed systems.

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It alleviates the developer from having to deal with explicit locking and thread management, making it easier to write correct concurrent and parallel systems. Actors were defined in the paper by Carl Hewitt but have been popularized by the Erlang language, and used for example at Ericsson with great success to build highly concurrent and reliable telecom systems.

Everything in Akka. NET is designed to work in a distributed setting: all interactions of actors use purely message passing and everything is asynchronous.

This effort has been undertaken to ensure that all functions are available equally when running within a single process or on a cluster of hundreds of machines.

The key for enabling this is to go from remote to local by way of optimization instead of trying to go from local to remote by way of generalization. See this classic paper for a detailed discussion on why the second approach is bound to fail. When an actor crashes, its parent can either restart or stop it, or escalate the failure up the hierarchy of actors. This enables a clean set of semantics for managing failures in a concurrent, distributed system and allows for writing highly fault-tolerant systems that self-heal.

Try Akka.

akka net vs

NET now! Follow our tutorial and build your first Akka. NET application today. What's new in Akka. NET v1. Get Started Now Read the documentation. Learn about Akka for the JVM here. High-level abstractions like Actors and FSM. Resilient by Design Write systems that self-heal. Extensible Use Akka. NET Extensions to adapt Akka to fit your needs.

Open Source Akka. NET is released under the Apache 2 license. Actor Model The Actor Model provides a higher level of abstraction for writing concurrent and distributed systems. Read more. Distributed by Default Everything in Akka.


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