Apache Storm compared to Hadoop

Question

How does Storm compare to Hadoop? Hadoop seems to be the defacto standard for open-source large scale batch processing, does Storm has any advantages over hadoop? or Are they co

Answer 1

Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing.

Since many sub systems exists in Hadoop ecosystem, we have to chose right sub system depending on business requirements & feasibility of a particular system.

Hadoop MapReduce is efficient for batch processing of one job at a time. This is the reason why Hadoop is being used extensively as a data warehousing tool rather than data analysis tool.

Since the question is related to only "Storm" vs "Hadoop", have a look at Storm use cases - Financial Services, Telecom, Retail, Manufacturing, Transportation.

1. Hadoop MapReduce is best suited for batch processing.
2. Storm is a complete stream processing engine and can be used for real time data analytics with latency in sub-seconds.

Have a look at this dezyre article for comparison between Hadoop, Storm and Spark. It explains similarities and differences.

It can be summarized with below picture ( from dezyre article)