Typesafe Announced New Releases of Akka and Slick

Date 2015/6/11 8:15:06 | Topic: Product News

Typesafe, the company behind Play Framework, Akka, and Scala, has announced the general availability of Akka Streams and Slick 3.0, new releases that address some of the major pain points for any Java or Scala developer working with streaming data.
For enterprises creating applications and microservices connected to streaming data sources, speed and reliability of data movement is critical. Akka Streams and Slick 3.0 bring the best of Reactive systems to streaming architectures (responsive, resilient, elastic and message driven), and today both have been released for general availability as part of the Typesafe Reactive Platform.

Akka (recent winner of the JAX Innovation Award for "Most Innovative Open Source Tech in 2015") is a toolkit for building message-driven applications. With Akka Streams, Akka has incorporated a graphical DSL for composing data streams, an execution model that decouples the stream's staged computation -- its "blueprint" -- from its execution (allowing for actor-based, single-threaded and fully distributed and clustered execution), type safe stream composition, an implementation of the Reactive Streaming specification that enables back-pressure, and more than 20 predefined stream "processing stages" that provide common streaming transformations that developers can tap into (for splitting streams, transforming streams, merging streams, and more).

Slick is a relational database query and access library, with a Functional Relational Mapping (FRM) paradigm that allows loose-coupling, minimal configuration requirements and and a number of other major advantages that abstract the complexities of connecting with relational databases. With Slick 3.0, Slick now supports the Reactive Streams API for providing asynchronous stream processing with non-blocking back-pressure. Slick 3.0 also allows elegant mapping across multiple data types, static verification and type inference for embedded SQL statements, compile-time error discovery, and JDBC support for interoperability with all existing drivers.

"The fundamental shift in data architectures today is how much data is 'in motion' and keeping the data flowing while limiting the resources that are consumed on the systems that the streams pass through," said Jonas Bonér. "We think that the streaming advances in Akka -- including the DSL, the higher level abstractions, and decoupling definition from execution -- make Akka Streams a very compelling toolkit for developers facing these challenges. And the functional relational mapping paradigm in Slick allows easy use of these patterns across even relational databases."

This article comes from Software Development Tools

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