Hadoop for Big Data
August 24, 2017

Hadoop for Big Data

Vinay Suneja | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Modules Used

  • Hadoop Common
  • Hadoop Distributed File System
  • Hadoop MapReduce
  • hive
  • pig
  • spark

Overall Satisfaction with Hadoop

[It was used] As a proof of concept to analyze a huge amount of data. We were building a product to analyze huge data and eventually sell that product to a utility.

Pros

  • Highly Scalable Architecture
  • Low cost
  • Can be used in a Cloud Environment
  • Can be run on commodity Hardware
  • Open Source

Cons

  • Its open source but there are companies like hortonworks, Cloudera etc., which give enterprise support
  • Lots of scripting still needed
  • Some tools in the hadoop eco system overlap
  • Positive as this is the future.
  • You can analyze data which you cannot do with traditional RDBMS.
  • Overall it is a win win if you implement it as a side car for doing new analytics without breaking your current operations and then eventually tying up with the eco system.
Amazon Redshift is some what closer to Hadoop. But to analyze Petabytes of data Hadoop as better performance.
  • To analyze a huge quantity of data at a low cost. It is definitely the future.
  • Machine learning with Spark is also a good use case.
  • You can also use AWS - EMR with S3 to store a lot of data with low cost.

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