- Jeffrey Dean (Google), Evolution of Systems Infrastructure at Google
- Mike Stonebraker (M.I.T.), A Vision and Research Program in “Big Data”, Big Data is (at least) Three Different Problems
- Stephen Wolfram (Wolfram Research)
- Eric Brewer (Google, UC Berkeley), Kubernetes and the Path to Cloud Native
- Jeff Hammerbacher (Cloudera), Emerging Technologies for Complex Extreme Scale Analytics
- Adam Kennedy (Apple), Corpus: Exabyte Datasets for Search and Machine Learning
- Oliver Ratzesberger (eBay) & Jeffrey Rothschild (Facebook), Operational Issues with Managing Large Database Clusters
- Fred Sanfilippo (Emory-Georgia Tech), Big Data and Healthcare
- Stephen Brobst (Teradata) & Tom Fastner (eBay), The Future of Analytics (tutorial)
- Greg Papadopoulos (New Enterprise Associates), Make it Big by Working Fast and Small: A VCs View of Large-Scale Success
- Dirk Duellmann (CERN), In Search of Higgs-Boson the Home-grown Way
- Gregory McAllister (Novartis), Drug Discovery in the Era of Big Data
- Kwan-Liu Ma (UC Davis), Visualizing Large, Complex Data
- Any Jain (Target), Transforming Retail with Multichannel Analytics
- Shirshanka Das (LinkedIn), Data Infrastructure at LinkedIn
- Frank Olken (NSF), Funding Big Data DBMS Technology at NSF: Research, Development, and Deployment
- Peter Breunig (Chevron), The Now and Later of Large Scale Computing at Chevron
- John Chambers (Stanford Statistics Dept), R in the World: Interfaces between Languages
- Susan Holmes (Stanford Statistics Dept), Extremely Large Data Challenges – What R Can and Can’t Do
- Daniel McCaffrey (Zynga), Analytics at Zynga
- Edmond Lau (Quora), Scaling Up Quickly on the Cloud
Video recordings of the talks (starting with the 5th XLDB) are available on YouTube.