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Popular White Papers, Datasheets & Reports

  • White Paper

    Introducing the Typesafe Reactive Platform

    Learn about the Typesafe technology ecosystem

    Get White paper
  • Report

    SURVEY RESULTS: APACHE SPARK

    Preparing for the next wave of Reactive Big Data

    Get Report
  • White Paper

    Introducing Typesafe ConductR

    A Reactive Application Manager for Operations

    Get White paper

Popular Case Studies & Stories

  • Case Study

    Modernizing from Monolith to Microservices

    The Guardian launches a digital-first strategy

    READ CASE STUDY
  • Case Study

    Achieving Unprecedented Resilience

    Walmart.ca experiences its first Black Friday with no downtime

    READ CASE STUDY
  • Community Story

    New Tweets Per Second Record, And How!

    A primary goal at Twitter is to make sure the service is always available

    Read Community Story

Latest E-Books & Videos

  • Latest E-Book Resources

    Big Data - Principles & best practices of...

    Big-Data

    Big-Data

    Big Data - Principles & best practices of...

    by Nathan Marz with James Warren

    Big Data - Principles and best practices of scalable realtime data systems teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to captur...

    Essential Slick

    Slick

    Slick

    Essential Slick

    by Richard Dallaway and Jonathan Ferguson

    Essential Slick is a guide to building a database application using the Slick library. It is aimed at Scala developers who need to become productive with Slick quickly. All registrants qualify for a Typesafe discount and will save...

    Spark in Action

    Spark

    Spark

    Spark in Action

    by Marko Bonaći and Petar Zečević

    Working with big data can be complex and challenging, in part because of the multiple analysis frameworks and tools required. Apache Spark is a big data processing framework perfect for analyzing near-real-time streams and discove...

    All E-Book Resources
  • Latest Video Resources

    A Deeper Look at Reactive Streams with Akka Streams 1.0 and Slick 3.0

    Webinar

    Reactive Reactive-Streams Akka Slick

    A Deeper Look at Reactive Streams with Akka Streams 1.0 and Slick 3.0

    with Endre Varga

    Reactive Streams 1.0.0 is now live, and so are our implementations in Akka Streams 1.0 and Slick 3.0.

    Reactive Streams is an engineering collaboration between heavy hitters in the area of streaming data on the JVM. With the Reactive Streams Special Interest Group, we set out to standardize a common ground for achieving statically-typed, high-performance, low latency, asynchronous streams of data with built-in non-blocking back pressure—with the goal of creating a vibrant ecosystem of interoperating implementations, and with a vision of one day making it into a future version of Java.

    Akka (recent winner of “Most Innovative Open Source Tech in 2015”) is a toolkit for building message-driven applications. With Akka Streams 1.0, Akka has incorporated a graphical DSL for composing data streams, an execution model that decouples the stream’s staged computation—it’s “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 for Scala that enables loose-coupling, minimal configuration requirements and abstraction of 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.

    Modernizing Your Aging Architecture: What Architects Need To Know About Going Reactive

    Webinar

    Reactive

    Modernizing Your Aging Architecture: What Architects Need To Know About Going Reactive

    with Michael Facemire & Kevin Webber

    When you need to react quickly to competitive threats or new line of business demands, but your existing architecture is anything but nimble, what do you do?

    Is it time to completely start over with a new enterprise architecture, or can you can augment your existing systems to become more resilient and responsive?

    Join Typesafe and Michael Facemire, Principal Analyst at Forrester Research in a discussion about how to leverage a Reactive architectural model to ensure your back-end infrastructure isn’t the limiting factor for your business success.

    Using Spark, Kafka, Cassandra and Akka on Mesos for Real Time Personalization

    Webinar

    Reactive Spark Akka

    Using Spark, Kafka, Cassandra and Akka on Mesos for Real Time Personalization

    with Patrick Di Loreto

    Listen to Patrick Di Loreto, R&D Engineering lead for William Hill as he reveals how this company is Going Reactive using Typesafe technologies with Cassandra, Kafka, Spark and Mesos to remain a leader in the gambling industry.

    All Video Resources

Podcast Channels

  • Typesafe Podcast Channel

  • Reactive Tech Talks Podcast Channel