My Big Data predictions for 2016


As 2016 is around the corner, the question is what this year will bring for Big Data. Here are my top assumptions for the year to come:

  • The growth for relational databases will slow down, as more companies will evaluate Hadoop as an alternative to classic rdbms
  • The Hadoop stack will get more complicated, as more and more projects are added. It will almost take a team to understand what each of these projects does
  • Spark will lead the market for handling data. It will change the entire ecosystem again.
  • Cloud vendors will add more and more capability to their solutions to deal with the increasing demand for workloads in the cloud
  • We will see a dramatic increase of successful use-cases with Hadoop, as the first projects come to a successful end

What do you think about my predictions? Do you agree or disagree?

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Published by

Mario Meir-Huber

I work as Big Data Architect for Microsoft. With this role, I support my customers in applying Big Data technologies - mainly Hadoop/Spark - for their use-cases. I also teach this topic at various universities and frequently speak at various Conferences. In 2010 I wrote a book about Cloud Computing, which is often used at German & Austrian Universities. In my home country (Austria) I am part of several organisations on Big Data.

2 thoughts on “My Big Data predictions for 2016”

  1. while I agree that classic RDBMS are of a shrinking species, I feel that NoSQL DB will be favoured over Hadoop. Hadoop is not suitable for workloads where a low latency is required. what I believe however is that Hadoop is the choice for their big data analytics stack. Spark will definitely do it in the area of data (pre) processing and predictive analytics due to its versatility.

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