Hadoop the solution to big data problems
December 01, 2015

Hadoop the solution to big data problems

Sudhakar Kamanboina | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Modules Used

  • Hadoop Distributed File System
  • Hadoop MapReduce

Overall Satisfaction with Hadoop

Hadoop is used by data center management team. Hadoop processes the metric data pushed by virtual machines. Hadoop's output is served to the analytics engine and respective actions are taken to maintain even load on machines.

Pros

  • Processing huge data sets.
  • Concurrent processing.
  • Performance increases with distribution of data across multiple machines.
  • Better handling of unstructured data.
  • Data nodes and processing nodes

Cons

  • Make Haadop lighweight.
  • Installation is very difficult. Make it more user friendly.
  • Introduce a feature that works with continuous integration.
Hadoop has a master slave architecture and comes with more features than Splunk.
Ask about how Hadoop fits in your environment and how fast it processes streaming data.

Using Hadoop

50 - Process system metric data which is generated each minute.
5 - People are well versed with Hadoop and are working on hadoop from last 3 years
  • Process container metrics
  • Products that are dependent on data
  • real time stream processing
  • Parallel processing of metrics
  • Map reduce increases the performance
  • Distribution of data on multiple nodes
  • In data centers to manage machines
  • Standalone architecture
  • Seamless integration

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