SQL-on-Hadoop for Analytics, Data Warehouse Offloading and Data Integration – What are My Options, What is the Future?

There are many options for providing SQL access over data in a Hadoop cluster, including proprietary vendor products along with open-source technologies such as Apache Hive, Cloudera Impala and Apache Drill; customers are using those to provide reporting over their Hadoop and relational data platforms, and looking to add capabilities such as calculation engines, data integration and federation along with in-memory caching to create complete analytic platforms. In this session we’ll look at the options that are available, compare database vendor solutions with their open-source alternative, and see how emerging vendors are going beyond simple SQL-on-Hadoop products to offer complete “data fabric” solutions that bring together old-world and new-world technologies and allow seamless offloading of archive data and compute work to lower-cost Hadoop platforms.

Mark Rittman
CTO, RittmanMead

Mark Rittman is co-founder of Rittman Mead, a specialist Data & Analytics consultancy with offices in the UK, USA and Europe. Mark has delivered data warehousing, business intelligence and now big data projects for clients around the world, has written two books on the topic and speaks at customer and industry events around the world.