The Pivotal team is heading out to see you at the Hadoop Summit in the San Jose Convention Center later this week. Considered the leading conference for the Apache Hadoop community, this two-day event features many of the Apache Hadoop thought leaders who will share successful Hadoop use cases, tips and tricks, and the roadmap for where Apache Hadoop is going in the enterprise.
As for Pivotal, we are excited to be a gold sponsor this year and are looking forward to meeting all of you at the sessions and on the show floor. This is our first year at Hadoop Summit as an independent company and we have lots of updates to share. For those new to Pivotal and what we have, be sure to ask our experts about the latest for the Hadoop products we have, including:
- Earlier this year, we announced HAWQ—a new technology with a 100x performance improvement over other Hadoop distributions and true SQL processing.
- Pivotal HD, our distribution of Hadoop that not only embraces HAWQ for faster processing, but also includes support for EMC Isilon OneFS Scale-Out NAS Storage for expandable elastic storage as well as Hadoop Virtualization Extensions (HVE) so Pivotal HD can run workloads on VMware’s vSphere.
- Our Spring Hadoop project and Spring XD project help our ecosystem of Spring Java developers become instantly more productive when developing workloads for Hadoop by providing a unified configuration model, APIs that simplify programming with HDFS, MapReduce, Pig, and Hive, and overall integration into the Spring platform including support for Spring Integration and Spring Batch.
- Pivotal Greenplum Database provides data scientists the advanced analytical programming support they need to analyze tera-to-petabyte data sets. Its massively parallel processing (MPP) capabilities can ingest up to 10 terabytes per hour (per rack with linear scalability to boot!) and offers new level of parallel analysis capabilities for mathematicians and statisticians including support for R, linear algebra, and machine-learning primitives.
Where to Find Us
This is where you can find us:
- In hall 2, Pivotal is in a double sided pod on the left side—just a bit further back from Yahoo! Here, you can learn about what we’re doing with Hadoop.
- VMware also had a pod, directly on the opposite side of the hall.
- On Wednesday from 2:05 to 2:45, join our own Gavin Sherry, Chief Strategist of Pivotal’s Data Fabric, for a panel on SQL and Hadoop with members from Cloudera, IBM, Hortonworks, and Datameer. The session title is called, “When Worlds Collide: SQL on Hadoop Pane”.
- On Thursday, we will have a 10 minute presentation in the Expo Hall from 1:20-1:30 PM on “Learn how Pivotal Enables you to Build Apps Leveraging Big and Fast Data”.
The panel will cover some hot topics—what is happening with the convergence of SQL and Hadoop, how open source technologies are being supported by vendors, how Hadoop is benefiting enterprises, and where the future is headed.
About Panelist Gavin Sherry
Gavin Sherry is Chief Strategist, Pivotal Data Fabric. In this role, he leads technology roadmap, architecture and R&D for Pivotal’s data processing technologies, including HAWQ, Pivotal’s industry leading SQL engine for Hadoop. Before Pivotal, Gavin was a major contributor to PostgreSQL and led efforts in open-source data processing technologies.
Special Strategy Sessions
To that end, VMware’s big data expert Joe Russell and EMC’s CTO Chuck Hollis will be combining to create special strategy sessions that will help pave out the future of running Hadoop workloads in the cloud. At Pivotal, we think this is an important new area of opportunity for Hadoop administrators and we’d like to see as many of you as possible be a part of these conversations. To sign up, please contact Chuck Hollis at chuck.hollis_AT_emc.com or Joe Russell at joerussell_AT_vmware.com. Be sure to tell them a little about yourself, your company and why you are interested. They will contact you directly to let you know availability for the sessions.
More Reading
If you aren’t coming to the Hadoop Summit, you might be interested in some of our previous articles on the topic of Hadoop:
- How to use Spring technologies with Hadoop
- Programming MapReduce, Hive, Pig, and Cascading
- Using the Pivotal 1000-node Hadoop Cluster
- 20+ Examples of Getting Results with Big Data
