Scala Stream

Fast Scala Feeds

Scala is a relatively new language that gained a lot of traction when Twitter started using it to power their scalable feeds. Our Scala client for Stream makes integrating feeds, activity streams and notifications systems into your Scala social network even faster.

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Build Better Apps, Faster

Stream is the fastest feed service
Stream is used for companies that need feeds that scale
Stream is the fastest feed service

Interactive Demo

Try the API

Scala Social Network

Stream is the leader in powering feeds, notifications systems and activity streams for some of the worlds most popular social networks. Scala powers much of the Twitter infrastructure and if you're looking for similar scalable feeds, Stream and scala are a great combo.

Working with Stream in the Scala language

The Scala language combines object-oriented with functional language features and runs on the Java Virtual Machine (JVM). It has grown in popularity over the years as it is considered a concise and enjoyable language to program with.

For web development two popular frameworks are Play and Scalatra. With Scala running on the JVM, well designed applications are ready for mission-critical production applications at enterprise scale. Furthermore, hosting options are plentiful with Heroku, Google Cloud Platform and Amazon Web Services being obvious choices.

Getting started: open source API Client

Our Client API for Scala is a contribution from the wonderful Sergey Kolbasov. It’s known as stream-scala and available on Github.

Further contributions in the form of issues, feature suggestions and pull requests are most welcome.

API for Feeds

Stream is an API for building scalable news feeds and activity streams. Try it out in this 5 minute interactive tutorial. To run the examples you'll need an API key. Register to continue...

var client = stream.connect('GET YOUR KEY');
var chrisFeed = client.feed('user', 'chris');
// Add the activity to the feed
actor: 'chris',
verb: 'add',
object: picture:10,
message: 'Working on improving the user experience of the Stream Dashboard...'
Flexible Implementation