Apache Mesos, Apache Hadoop, Apache Spark + Custom Enterprise Applications: This stack combined is greater than the sum of each of the pieces of this stack. Mesos can manage resources across an entire data center, Hadoop provides a distributed data store and scalable data processing, and Spark delivers great in-memory and disk-based performance of data processing as well as streaming capabilities. Couple all of that with custom enterprise applications, and the data center turns into a well-oiled machine. When combined, this software stack delivers unlimited flexibility for the entire data center.
Jim Scott is the cofounder of the Chicago Hadoop Users Group. As a cofounder Jim has helped build the Hadoop community in Chicago for the past 4 years. He has implemented Hadoop in three different companies supporting enterprise use cases from managing Points Of Interest for mapping applications, Online Transactional Processing in advertising, as well as full data center monitoring and general data processing. His work with high-throughput computing at Dow Chemical was a precursor to more standardized big data concepts like Hadoop.
For exhibition and sponsorship opportunities, email email@example.com
For information on trade opportunities with O'Reilly conferences, email firstname.lastname@example.org
For media-related inquiries, contact Maureen Jennings at email@example.com
View a complete list of Strata + Hadoop World contacts
©2015, O’Reilly UK Ltd • (800) 889-8969 or (707) 827-7019 • Monday-Friday 7:30am-5pm PT • All trademarks and registered trademarks appearing on oreilly.com are the property of their respective owners. • firstname.lastname@example.org
Apache Hadoop, Hadoop, Apache Spark, Spark, and Apache are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries, and are used with permission. The Apache Software Foundation has no affiliation with and does not endorse, or review the materials provided at this event, which is managed by O'Reilly Media and/or Cloudera.