October 2013 Release: Expanded DataSense connectivity


I’m pleased to announce the availability of the Oct 2013 release of Studio and CloudHub. It greatly expands our support for DataSense in our Anypoint™ Connectors, improves connector usability through auto-paging of result sets, and includes many other improvements. 

Expanded DataSense capabilities

We believe that metadata-driven design is the number one productivity enhancer for SaaS to on-premise integration. Therefore, the number one goal of the release was to greatly expand the number of connectors which support DataSense and DataSense Query Language. To this end, we’ve made many improvements to Mule Studio, Anypoint Connectors and the CloudHub Mule Runtime (see below) to make these connectors work seamlessly. Another key feature we’ve added is an advanced editor for DataSense Query Language. It offers the ability to create advanced, complex expressions using for auto-suggest to make extracting data from your applications easier than ever.

The expanded list of connectors which now supports DataSense includes:

Additionally, we’re updating more and more connectors all the time, with many more coming before the end of the year.

Auto-paging and Anypoint Connectors

If you’ve ever worked with large data sets, you know that it can be difficult to deal with multiple pages of results. Fundamentally, we want to enable customers to work with data in a declarative way, not a procedural way. This means we don’t want to force you to write a for-loop to get more results– it should just work!

For this, we’ve introduced auto-paging for connectors. When querying data using DataSense Query Language or other connector operations, connectors can now return an iterator which automatically handles paging. This allows you to stream infinite results-sets right into DataMapper, then into something like a CSV file without having to worry about out of memory errors.

CloudHub Mule Runtime

Previously, we referred to our 2-month release artifacts by the project’s internal code name (e.g. Andes). With the latest release, we have adjusted the naming of the runtime to “CloudHub Mule Runtime (month year)”. This makes it more clear that if you use this runtime with the latest features (e.g. DataSense Query Language), you can only deploy to CloudHub. The features available in the CloudHub Mule Runtime releases will be made available in the full, Mule 3.5.0 release early next year. If you want to work in hybrid environments, you can continue to use Mule 3.4 to deploy applications on-premises or to CloudHub. Read more about our new Release Strategy.

Other Improvements

We’ve also made some other improvements:

  • Control Polling from the Debugger: start and stop polling from the debugger to easily test integrations when you have a large number of synchronizations.
  • Import/Export reliability: robustness has been improved and many bugs have been fixed.
  • Bug fixes: we have written hundreds of additional tests over the last two months so, in terms of quality, this is our best release yet!

For more information please consult the release notes. As always, we look forward to your feedback!

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