Overall Satisfaction with Hadoop
I have been working with Hadoop since last year. It is very user friendly. Hadoop was used by the data center management team. It allows distributed processing of huge amount of data sets across clusters of computers using simple programming models.
- Apache Spark and Apache Flink
Apache Spark has an in memory processing model, making it powerful for lightning fast data processing. Apache Spark also exposes Scala and Python in APIs which is one of the most commonly used programming languages in data analytic and data processing domains.
Hadoop is really very useful when dealing with big data.
Evaluating Hadoop and Competitors
- Product Features
- Product Usability
I used hadoop and found it really useful while working with bigger data sets. I used Hadoop for my project to get insight of different patterns from given data set. It was easy and user friendly.
I'll be looking at scalability, reliability. At the same time it will be good to have small learning curve.
I found it really useful during my academic projects. Data handling for large data sets was easy with Hadoop. It used to work really fast for bigger data sets. I found it reliable.
Like to use
Easy to use
Quick to learn
Feel confident using
Requires technical support
Lots to learn
- Processing huge data sets with good performance
- Distributed data handling with multiple nodes
- Small Learning curve
- Using Hdoop is a heavy weight process
- Installation is a little tricky for newbees
- Not suitable for dynamic data sets
Yes, but I don't use it