[Webinar Archive] Moving Away from MapReduce to SQL on Hadoop

/, Webinar/[Webinar Archive] Moving Away from MapReduce to SQL on Hadoop
Moving Away from MapReduce to SQL Webinar
MapReduce is the standard mechanism to retrieve data from Hadoop-based Big Data implementations. However, it is quickly going out of fashion given the complexity and cost of creating and maintaining MapReduce jobs and developers are looking to move to SQL-based solutions. Watch our webinar archive to learn aboujt replacing MapReduce with SQL to realize the following benefits: 
  • Faster app development
  • Leverage SQL Tools and Resources
  • Minimize dependency on Data Scientists and Java Programmers
  • Do more with Big Data


Given the strategic nature of Big Data solutions and the power of MapReduce, you need to carefully choose the right SQL-on-Hadoop solution to support all your Big Data application needs. 

Learn how to:

  • Understand limitations and complexities of MapReduce
  • Know what to look for in a SQL-on-Hadoop solution
  • Strategize which types of jobs to move to SQL and which ones to keep in MapReduce
  • Ensure performance with SQL

Who should watch?

  • Big Data developers, architects and IT managers
  • Product and line of business owners
  • CIOs and operations executives

Esgyn Expert Panel

Panelist – Dave Birdsall, Sr. Staff Member, Esgyn

Dave has worked on relational database engines for 30 years. He has made contributions to execution engines, DDL and metadata management, online utilities, stored procedures, manageability and most recently in query optimization. Database is a rich field; it has never been boring. He loves building stuff, and working in these areas has made for a joyful career. Dave is a committer for Apache Trafodion project.

Panelist – Hans Zeller, Sr. Staff Member, Esgyn

Hans has worked on relational database engines for all of his professional career. He developed a hash join algorithm in the late 1980s, then worked on the rule and cost-based optimizer engine that powers EsgynDB / Apache Trafodion and its predecessors (Tandem NonStop SQL and HP Neoview). More recently he was involved with the MapReduce-style user-defined functions (UDFs) in Apache Trafodion.  Hans is a committer for Apache Trafodion project.

Host – Kevin DeYager, Product Marketing Manager, Esgyn

Kevin has held product management and marketing roles for application development tools to servers to database solutions.  His efforts in database has spanned workloads from business intelligence and analytics to online transaction processing.  A proponent of open source software since the late 1990s, Kevin is a contributor to the Apache Trafodion project.

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