Can Apache Flink Replace Apache Spark?

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Can Apache Flink Replace Apache Spark?
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• Apache Flink and Apache Spark are both
  distributed and open-sourced processing
  frameworks built for reducing the latencies of
  the Hadoop MapReduce in quick data processing. A
  very common misconception exists in this field
  and that is Apache Flink will soon be replacing
  Apache Spark. Is it really possible for both
  these huge data technologies to co-exist and
  serve the requirements of fast and fault-tolerant
  processing.

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• Flink and Spark might seem quite similar to
  individuals who have not worked with any of these
  and are quite familiar with Hadoop. However, it
  is quite obvious that such individuals will
  probably feel that the progress of the Apache
  Flink is superfluous.

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• Nevertheless, Flink has managed to remain ahead
  in the competition mainly because of the stream
  processing feature that it possesses. This
  feature helps it to manage and process large rows
  of data in real time. This is something that is
  not possible with Apache Spark which takes the
  batch processing methodology into consideration.
  This is one feature that makes Apache Flink
  better and faster in comparison to Apache Spark.

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• As per studies conducted by IBM, there are
  approximately 2.5 quintillion bytes of data
  created regularly. It is also to be noted that
  this rate of generating data is constantly
  increasing at a very fast pace. Taking things
  from another perspective, around 90 of data
  existing throughout the world was processed in
  the last couple of years in spite of the fact
  that the World Wide Web is accessible to the
  public for more than two decades now.

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• With the growth of the internet, there has been a
  considerable growth in the number of users and
  there has been an ever-increasing demand for
  valid content paving the path for Web 2.0 in the
  last ten years. This was for the very first time
  that the users were given the flexibility of
  creating their very own data on the internet.
  This data was readily consumable by the audiences
  who were data hungry.

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• Both Apache Flink and Apache Spark Training In
  Bangalore are next generation Big Data tools
  grabbing huge industry attention. They serve as
  the best solutions for different Big Data issues.
  However, it is to be noted that in comparison to
  Spark, Flink is faster because of its underlying
  architecture. Spark has string community support
  along with several contributors. Nevertheless, as
  far as streaming capabilities are concerned,
  Flink serves to be far better that Spark and even
  possesses native support for the purpose of
  streaming. Spark is the 3G of Big Data while
  Flink is the 4G.

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