Streaming Hadoop HBase Case Study: Turbo-charging Hadoop for real-time machine data analytics

Accelerating Hadoop HBase to process live, high velocity unstructured data streams delivers the low latency, streaming operational intelligence demanded by today's real-time businesses. Hadoop has been the driving force behind Big Data Analytics but as the technology hits the mainstream, many industries are seeking to take a step further and eliminate latency from their business completely. With the emergence of both streaming and the SQL language as key components of Big Data architectures, this presentation discusses how to extend HBase with streaming SQL queries. Streaming queries effectively extend the Hadoop HBase platform out to the edge of the network, making it possible to query unstructured log file, sensor and network machine data sources on the fly and in real-time.

Damian Black has over twenty-five years in the software infrastructure business. Damian started his career at Hewlett-Packard in HPLABS at their European research labs, and went on to run a European-wide middleware solutions business before moving to the US. For HP in the US he led the team that pioneered IP Mediation – a real-time technology for analytics and billing in Telecomm, becoming market leader. He later moved to XACCT as VP Product Management, acquired by Amdocs to power its real-time data mediation. Damian was next VP Sales and Business Development for Followap, a Sequoia funded company, until it was acquired by NeuStar. Followap was the market leader in mobile Instant Messaging and Presence powering Vodafone’s IM service among others, continuing Damian’s career in real-time middleware.