**IMPORTANT: As of Akka 1.1, Akka Future, CompletableFuture and DefaultCompletableFuture have all the functionality of DataFlowVariables, they also support non-blocking composition and advanced features like fold and reduce, Akka DataFlowVariable is therefor deprecated and will probably resurface in the following release as a DSL on top of Futures.**
Akka implements `Oz-style dataflow concurrency <http://www.mozart-oz.org/documentation/tutorial/node8.html#chapter.concurrency>`_ through dataflow (single assignment) variables and lightweight (event-based) processes/threads.
Dataflow concurrency is deterministic. This means that it will always behave the same. If you run it once and it yields output 5 then it will do that **every time**, run it 10 million times, same result. If it on the other hand deadlocks the first time you run it, then it will deadlock **every single time** you run it. Also, there is **no difference** between sequential code and concurrent code. These properties makes it very easy to reason about concurrency. The limitation is that the code needs to be side-effect free, e.g. deterministic. You can't use exceptions, time, random etc., but need to treat the part of your program that uses dataflow concurrency as a pure function with input and output.
The best way to learn how to program with dataflow variables is to read the fantastic book `Concepts, Techniques, and Models of Computer Programming <http://www.info.ucl.ac.be/%7Epvr/book.html>`_. By Peter Van Roy and Seif Haridi.
The documentation is not as complete as it should be, something we will improve shortly. For now, besides above listed resources on dataflow concurrency, I recommend you to read the documentation for the GPars implementation, which is heavily influenced by the Akka implementation: