What is the point of Hadoop? It’s a question we’ve asked a few times on this blog, and continues to be a significant question asked by users, investors and vendors about Apache Hadoop. That is why it is one of the major questions being asked as part of our 451 Research 2013 Hadoop survey.

As I explained during our keynote presentation at the inaugural Hadoop Summit Europe earlier this year, our research suggests there are hundreds of potential workloads that are suitable for Hadoop, but three core roles:

• Big data storage: Hadoop as a system for storing large, unstructured, data sets
• Big data processing/integration: Hadoop as a data ingestion/ETL layer
• Big data analytics: Hadoop as a platform new new exploratory analytic applications

And we’re not the only ones that see it that way. This blog from Cloudera CTO Amr Awadallah outlines three very similar, if differently-named use-cases (Transformation, Active Archive, and Exploration).

In fact, as I also explained during the Hadoop Summit keynote, we see these three roles as a process of maturing adoption, starting with low cost storage, moving on to high-performance data aggregation/ingestion, and finally exploratory analytics.

As such it is interesting to view the current results of our Hadoop survey, which show that the highest proportion of respondents that have implemented or plan to implement Hadoop (63%) for data analytics, followed by 48% for data integration and 43% for data storage.

This would suggest that our respondents include some significantly early Hadoop adopters. I look forward to properly analysing the results to see what they can tell us, but in the meantime it is interesting to note that the percentage of respondents using Hadoop for analytics is significantly higher among those that adopted Hadoop prior to 2012 (88%) compared to those that adopted in in 2012 or 2013 (65%).

To give your view on this and other questions related to the adoption of Hadoop, please take our 451 Research 2013 Hadoop survey.