SpringSource announce next Big Data steps in Spring XD
After the launch of Spring for Apache Hadoop in February, SpringSource reveal their next move. Will it be Pivotal?
Following the successful launch of their
Hadoop project in February, SpringSource
have unveiled their next steps into the world of Big
Spring XD (shorthand for eXtreme Data and not
the emoticon) is set to tackle “Big Data complexity” according to
Having spent the last year crafting the
groundwork for Spring for Apache Hadoop, allowing it
to run MapReduce jobs and create
helper classes for offshoot projects like Hive and Pig,
Spring XD is focused on dealing with common Big Data use
The reveal of Spring XD comes mere hours
Pivotal launches, the new
“platform” for VMware and EMC’s line of
big data and cloud products.
Fisher outlines four ambitious key goals for
Spring XD, which centre around “high throughput” data ingestion
and the ability to export to relational
and NoSQL databases. The red hot trend of real-time analytics is
also set to be addressed with Spring XD set to include “real-time
analytics at ingestion time” - but how
advanced that will be remains to be seen. The project will also
introduce a Hadoop workflow management system through batch jobs,
which will interact with fellow Hadoop projects such as Cascading,
as well as standard enterprise systems.
Despite many of these
use cases being covered in SpringSource’s Spring Data book (which
has sample code on Github),
Fisher believes the arrival of Spring XD will provide a
“consistent” and “familiar” model to Spring developers. Further
down the roadmap, Spring XD will provide an out-of-the-box
executable server, pluggable modules and a model for collecting
instances on or off the Hadoop cluster.
can be forked right away, however.
Fisher admits that the project is in its infancy, but wanted the
announcement to come out as soon as possible to allow community
members to get their teeth into it. Further milestones are expected
in May, June and August before a release candidate arrives in