Albany, NY -- (SBWire) -- 06/08/2018 --You probably did not hear it here first. Spark has been making waves in big data platforms for a while now. Apache Spark is an open source processing engine used for running spark applications with 100 times faster speed than Big data Hadoop and 10 times faster than accessing data from disk. Due to its advanced features and functionality, popularity of Apache Spark has increased within the developers, integrators and end-users. Spark is the future of big data and the future of the future looks bright.

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Spark has evolved as an effective alternative for Hadoop. Its popularity has increased recently for on-disk sorting, involving large data sets. Apache Spark is the one most active projects of Apache and its future scope will be long lasting and considered as future of Big Data Platform because High compatibility with Hadoop, Hadoop is dwindling while Spark is sparking, Increased access to Big Data, High demand for Spark professionals, Diverse, Apache Spark to make Big Money.

Demand for Apache Spark is projected to rise in the near future as the popularity of fog computing is anticipated to increase.

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Is Spark replacing Hadoop?

May be, because its speed of processing is high compared to Hadoop as a result of its bottom-up engineering. Its popularity has increased recently for on-disk sorting, involving large data sets. But there are some disadvantages of spark such as no support for Real-time Processing, Problem with Small File, No File Management System, Expensive, Less number of Algorithms.

The global Apache Spark market is expected to exhibit an intense level of competition in the coming years. The quest of market players to capture a greater market share has got them to a situation wherein a single player's moves are expected to prompt a response from others. Major players associated with the Apache Spark market include IBM Corporation, Databricks, MapR Technologies Inc., Qubole and Cloudera

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