16.SQL on Hadoop: SQL+NoSQL in one place, which translates into Drill + MapRDB


Details
Agenda:
• 17.45: eat, drink, socialize
• 18.15: First talk: OLTP and Datawarehouse in one place: SQL on Hadoop by M.C. Srivas
Speaker: M.C. Srivas, CTO and Co-founder of MapR
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Srivas ran one of the major search infrastructure teams at Google where GFS, BigTable and MapReduce were used extensively. He wanted to provide that powerful capability to everyone, and started MapR on his vision to build the next-generation platform for semi-structured big data. His strategy was to evolve Hadoop and bring simplicity of use, extreme speed and complete reliability to Hadoop users everywhere, and make it seamlessly easy for enterprises to use this powerful new way to get deep insights. That vision is shared by all at MapR. Srivas brings to MapR his experiences at Google, Spinnaker Networks, Transarc in building game-changing products that advance the state of the art.
Srivas was Chief Architect at Spinnaker Networks (now NTAP) which built the industry's fastest single-box NAS filer, as well as the industry's most scalable clustered filer. Previously, he managed the Andrew File System (AFS) engineering team at Transarc (now IBM). AFS is now standard classroom material in operating systems courses. While not writing code, Srivas enjoys playing tennis, badminton and volleyball. M.C. has an MS in Computer Science from University of Delaware, and a B.Tech. in electrical engineering from IIT Delhi.
Additional information
- RSVP to the meetup
Please RSVP to this meetup, since we need to put everybody on a guest list for entering the Spotify office. The event will be held in the cafeteria of the Spotify office, so don’t go to the normal entrance but to the 11th floor.
- Pizza and drinks
Thanks to MapR, pizza and beverages will be available for the participants during the meetup. This is another reason to RSVP to this meetup, if you are willing to come - it will help us to estimate the number of pizzas and drinks based on declared attendance.

16.SQL on Hadoop: SQL+NoSQL in one place, which translates into Drill + MapRDB