Item: Apache Hadoop
Rating: 10
Author: Tom Thomas

Use Cases and Deployment Scope

The company I worked at used Hadoop clusters for processing huge datasets. They had several nodes for both production and per-production nodes. It allowed distributed processing of data across several clusters with an easy to use software model. It is used by the Systems and IT department at my company.

Pros and Cons

HDFS provides a very robust and fast data storage system.
Hadoop works well with generic "commodity" hardware negating the need for expensive enterprise grade hardware.
It is mostly unaffected by system and hardware failures of nodes and is self-sustained.

While its open source nature provides a lot of benefits, there are multiple stability issues that arise due to it.
Limited support for interactive analytics.

Return on Investment

Reduced costs of hardware due to support for generic hardware
Improved time and cost of data analysis

Other Software Used

Apache Pig, Apache Hive, Apache Sqoop

Likelihood to Recommend

Hadoop is a very powerful tool that can be used in almost any environment where huge scale processing of data across clusters is required. It provides multiple modules such as HDFS and MapReduce that will make managing and analyzing said data reliable and efficient. Hadoop is a new and constantly evolving tool, and hence it needs users to be on top of it all the time.

Products Replaced

Key Differentiators

Price
Product Features
Product Usability
Product Reputation
Vendor Reputation
Analyst Reports
Third-party Reviews

Hadoop is the Perfect Enterprise tool for Big Data

Modules Used

Overall Satisfaction with Hadoop