An interesting read given my post today on Activity Streams:
A core feature of the real-time web is the continuously updating real-time streams of information. These streams are commonly generated by social networks and with the continued uptake of social networking the amount of information is only going to increase. This will continue to introduce opportunities for companies to create products and services that extract value from that vast amount of data. Some of the most common services built around these streams include trend and sentiment analysis, data storage, aggregation, sorting, search and filtering. DataSift is a service that offers a host of exciting features including the ability to let users browse, build and share their own real-time streams using social media data drawn from a host of sources.
DataSift launched its Alpha service at TechCrunch Disrupt in September and describe it as a “real time social media filtering engine.” The initial buzz around DataSift was generated when Twitter agreed to give them access to the Twitter firehose, but they now have access to a much wider range of data including the Google Buzz, MySpace, SixApart, WordPress, Facebook and Digg. These sources of data within DataSift, sometimes called input services, are defined as Targets in the DataSift knowledge base.