Prevailing wisdom has long held that transactional and analytical data processing must occur in separate data stores.
However, hidden costs of architectural complexity, combined with technical challenges facing modern enterprises, call for versatile, multi-purpose solutions rather than separate specialized solutions.
As infrastructure advances to meet user expectations, modern database design erodes the barriers between OLTP and OLAP, giving way to a third kind of database that converges transaction and analytic data processing.
Businesses need to move from offline batch processing to real-time data pipelines so they can provide personalization, detect anomalies, analyze data continuously, and manage business operations as they happen.
Advances with in-memory storage and distributed architectures enable businesses to process more data faster than ever before, with projects like Spark and Hadoop spawning ecosystems of complementary technologies.
Yet, enterprises require a hub for unifying big data processing technologies that allows them to work in concert.
In this session, MemSQL CEO Eric Frenkiel will discuss the need for simplicity in enterprise data architecture, the convergence of transactions and analytics, and what is required to operationalize Spark and Hadoop in the enterprise.
About Eric Frenkiel (MemSQL):
Eric Frenkiel co-founded MemSQL and has served as CEO since inception. Before MemSQL, Eric worked at Facebook on partnership development. He has worked in various engineering and sales engineering capacities at both consumer and enterprise startups. Eric is a graduate of Stanford University’s School of Engineering. In 2011 and 2012, Eric was named to Forbes’ 30 under 30 list of technology innovators.