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Hadoop is very popular and demanding nowadays in the tech-market, and going forward for any interview related to Hadoop of course the first question will, what is differences between MapReduce and traditional RDBMS. Of-course the popular question is what is MapReduce? We will see later about MapReduce in separate post, here I am going to show you the key differences between MapReduce and RDBMS.

MapReduce Vs RDBMS

  1. MapReduce suits in an application where the data is written once and read many times like in your Facebook profile you post your photo once and that picture of your seen by your friends many times, whereas RDBMS good for data sets that are continuously updated.
  2. The RDBMS is suits for an application where data size is limited like it's in GBs,whereas MapReduce suits for an application where data size is in Petabytes.
  3. The RDBMS accessed data in interactive and batch mode, whereas MapReduce access the data in batch mode.
  4. The RDBMS schema structure is static, whereas MapReduce schema is dynamic.
  5. The RDBMS suits with structure data sets, whereas MapReduce suits with un-structure data sets.
  6. The RDBMS scaling is nonlinear, whereas MapReduce is linear.

That's it, about the key differences for Hadoop interview question.
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