Concurrency, co-existence and complexity: Three keys to implementing SQL on Hadoop in the real world
Date: This event took place live on February 02 2016
Duration: Approximately 60 minutes.
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SQL has long been the most widely used language for big data analysis. The SQL-on-Hadoop ecosystem is loaded with both commercial and open source alternatives, each offering tools optimized for various use cases. Fledgling analytical engines are in incubation, but are they ready to become full-fledged members of your enterprise infrastructure? Are they ready to fly?
In the real world, enterprises must understand their needs and select a SQL-on-Hadoop solution that addresses them. Points to consider: What are your analytics use cases—will a single user be working on data discovery or will multiple users perform daily analytics? Will you need to modify SQL to adjust to different deployment scenarios, or does a single solution exist for on-premises, Cloud, and Hadoop? Can a single solution support a variety of workloads from quick-hit dashboards to complex, resource-intensive, join-filled queries?
In this webcast, you will learn:
About Satish Sathiyavageswaran, Solutions Architect – Hewlett Packard Enterprise
Satish Sathiyavageswaran is a Solutions Architect for Hewlett Packard Enterprise Big Data Platform. He has been working with Hewlett Packard Enterprise for more than 6 years. His primary focus is working on Proof of Concepts for projects involving Vertica SQL on Hadoop and its integration with other applications in the Hadoop eco system.
About Hochan Won, Corporate Systems Engineer – Hewlett Packard Enterprise
Hochan Won is a Corporate Systems Engineer for HPE Big Data Platform. She has been working with HPE Vertica for the last two years. Prior to HPE, she was a Database Administrator for over 13 years, working with different database platforms, such Oracle, IBM Informix/Netezza, and SQL Server.