1 / 13

Spark vs Hadoop: Which Big Data Framework to Choose?

This is a comparison presentation between two popular big data frameworks, Hadoop and Spark. Here you will get detailed information about their pros and cons, alongside getting familiar with different factors to consider during u2018Spark vs Hadoopu2019 battle.

emily_10
Download Presentation

Spark vs Hadoop: Which Big Data Framework to Choose?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Spark vs Hadoop: Which Big Data framework to choose?

  2. Choosing between Spark and Hadoop big data frameworks can be a tough task for an Entrepreneur or developer. But not when you consider these factors for comparison.

  3. Architecture Hadoop, unlike Spark, has two prime elements YARN and HDFS to manage diferent data storage and resource allocation processes. This makes Hadoop’s architecture capable of delivering better solutions that that of Spark. Hadoop 1 Spark 0

  4. Ease of Use In comparison to Apache Hadoop, Spark ofers more user-friendly APIs and interactive mode facilities to mobile app development companies. This eases the process of learning and using Spark. https://appinventiv.com/ Hadoop 0 Spark 1

  5. Data Processing While Hadoop ofer only batch processing, Spark avails the opportunity to perform diferent types of data processing, including interactive, graph, iterative, and batch processing. Hadoop 0 Spark 1

  6. Fault Tolerance In case of Spark, one has to begin from scratch if a process fails in between. But, in the case of Hadoop, one can continue from the point of crash. Something that proves that Hadoop ofers higher levels of fault tolerance. Hadoop 1 Spark 0

  7. Compatibility When it comes to compatibility, both Hadoop and Spark big data frameworks provides higher grades of compatibility. They act as standalone applications, as well as, work together by supporting each others' data sources and file formats. Hadoop 1 Spark 1

  8. Performance Spark, when compared to Hadoop, runs 10 times faster on disk and 100 times in-memory. Also, it is able to manage 100TB of data in 3 times faster than Apache Hadoop. Hadoop 0 Spark 1

  9. Security Unlike Spark, Hadoop encourages Kerberos authentication, third-party authentication, conventional file permissions, and access control lists. Something that makes it easier for Hadoop big data framework to deliver higher security. Hadoop 1 Spark 0

  10. Cost-Efectiveness When compared to Hadoop, Apache Spark requires more memory on disk and has less developers in the market. This makes mobile application development using Big data framework expensive. Hadoop 1 Spark 0

  11. Future Possibilities Though both Hadoop and Spark are used by big companies, the former is expected to grow with a CAGR of 65.6% in between 2018 and 2025, when compared to Spark that will flourish with a CAGR of 33.9% only. Hadoop 1 Spark 0

  12. For a detailed information about this topic, please refer to this blog: https://appinventiv.com/blog/spark-vs-hadoop-big-data-frameworks/ Spark vs Hadoop: Which Big Data Framework Will Elevate Your Business?

  13. Contact Us Appinventiv Technologies sales@appinventiv.com +91 8826909998 +1-646-585-0501 https://www.facebook.com/Appinventiv/ https://twitter.com/appinventiv?lang=en https://www.instagram.com/appinventiv/?hl=en https://www.linkedin.com/company/appinventiv/?originalSubdomain=in

More Related