Among the many calls we have fielded from users, investors and vendors about Apache Hadoop, the most common underlying question we hear could be paraphrased ‘what is the point of Hadoop?’.
It is a more fundamental question than ‘what analytic workloads is Hadoop used for’ and really gets to the heart of uncovering why businesses are deploying or considering deploying Apache Hadoop. Our research suggests there are three core roles:
- Big data storage: Hadoop as a system for storing large, unstructured, data sets
- Big data integration: Hadoop as a data ingestion/ETL layer
- Big data analytics: Hadoop as a platform new new exploratory analytic applications
While much of the attention for Apache Hadoop use-cases focuses on the innovative new analytic applications it has enabled in this latter role thanks to its high-profile adoption at Web properties, for more traditional enterprises and later adopters the first two, more mundane, roles are more likely the trigger for initial adoption. Indeed there are some good examples of these three roles representing an adoption continuum.
We also see the multiple roles playing out at a vendor level, with regards to strategies for Hadoop-related products. Oracle’s Big Data Appliance (451 coverage), for example, is focused very specifically on Apache Hadoop as a pre-processing layer for data to be analyzed in Oracle Database.
While Oracle focuses on Hadoop’s ETL role, it is no surprise that the other major incumbent vendors showing interest in Hadoop can be grouped into three main areas:
- Storage vendors
- Existing database/integration vendors
- Business intelligence/analytics vendors
The impact of these roles on vendor and user adoption plans will be reflected in my presentation at Hadoop World in November, the Blind Men and The Elephant.
You can help shape this presentation, and our ongoing research into Hadoop adoption drivers and trends, by taking our survey into end user attitudes towards the potential benefits of ‘big data’ and new and emerging data management technologies.