Big Data > Spark > Differences Hadoop VS Spark

What are the differences between Hadoop and Spark?

• Faster Processing: Hadoop processes data using MapReduce, which is slower due to disk-based operations, while Spark processes data in-memory, making it up to 10 times faster.
• Processing Type: MapReduce supports only batch processing, whereas Spark supports both batch processing and real-time processing.
• Code Efficiency: Hadoop is written in Java and generally requires more lines of code, making development and execution slower. Spark, written in Scala, needs fewer lines of code and offers faster execution.
• Security & Integration: Hadoop uses Kerberos authentication, which is secure but difficult to manage. Spark supports easier authentication via a shared secret and can also run on YARN, leveraging Kerberos-based security when needed.

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