Top 5 Concerns of Big Data Hadoop Implementation

Apache Hadoop is an open-source, java-based programming framework meant to process large data sets in a distributed environment. Hadoop has created a lot of Big Data hype in digital arena, with many viewing it as the best platform for handling high volume data infrastructures. Sorting of Big Data offers great opportunities to companies to increase their ROI by targeting or retargeting right customers.

Big Data has a lot of virtues, but many companies are wary of Big Data Hadoop implementation. In this blog, I have discussed major constraints that make Hadoop inappropriate for Big Data.

But first have a quick look why Hadoop is touted as a standard platform for Big Data

• High data storage and processing speed

• Scalability

• Flexibility

• Free open-source framework

Now let’s talk about negative points of Big Data Hadoop implementation

• Not suitable for small data

• Security and Vulnerability

• Stability Issues

Here is not the end...For full blog about Top 5 Concerns of Big Data Hadoop Implementation, kindly visit Evontech.