Understand the Challenges of Delivering Hybrid Transaction/Analytic Processing on Hadoop

The Challenges of Delivering Hybrid Transactions/Analytical Processing

The database pendulum is in full swing. Ten years ago, web-scale companies began moving away from proprietary relational databases to handle Big Data use cases with NoSQL and Hadoop. Now, for a variety of reasons, the pendulum is swinging back toward SQL-based solutions. What many companies really want is a system that can handle all of their operational, OLTP, BI, and analytic workloads. Could such an all-in-one database exist?

This O’Reilly report, authored by Rohit Jain, CTO of Esgyn Corporation, examines this quest for database nirvana, or what Gartner recently dubbed Hybrid Transaction/Analytical Processing (HTAP). Rohit takes an in-depth look at the possibilities and the challenges for companies that long for a single query engine to rule them all.

With this report, you’ll explore:

• The challenges of having one query engine support operational, BI, and analytical workloads
• Efforts to produce a query engine that supports multiple storage engines
• Attempts to support multiple data models with the same query engine
• Why an HTAP database engine needs to provide enterprise-caliber capabilities, including high availability, security, and manageability
• How to assess various options for meeting workload requirements with one database engine, or a combination of query and storage engines

Rohit Jain is co-founder and CTO at Esgyn, an open source database company. He provided the vision behind Apache Trafodion, an enterprise-class MPP SQL Database for Big Data, donated to the Apache Software Foundation by HP in 2015. A veteran database technologist over the past 28 years, Rohit has worked for Tandem, Compaq, and Hewlett-Packard in application development and massively parallel distributed database systems.