More detailed description and feature details you can find in the above link:
- Extreme low cost per byte
- Very high bandwidth to support MapReduce workloads
- Rock solid data reliability
Some of the reasons organizations use Hadoop is its’ ability to store, manage and analyze vast amounts of structured and unstructured data quickly, reliably, flexibly and at low-cost.Scalability and Performance– distributed processing of data local to each node in a cluster enables Hadoop to store, manage, process and analyze data at petabyte scale.Reliability– large computing clusters are prone to failure of individual nodes in the cluster. Hadoop is fundamentally resilient – when a node fails processing is re-directed to the remaining nodes in the cluster and data is automatically re-replicated in preparation for future node failures.Flexibility– unlike traditional relational database management systems, you don’t have to created structured schemas before storing data. You can store data in any format, including semi-structured or unstructured formats, and then parse and apply schema to the data when read.Low Cost– unlike proprietary software, Hadoop is open source and runs on low-cost commodity hardware.
There are many features of hadoop. Some of the most important features of Hadoop are:
ITs source code is open. You change its code accroding to your requirement
Can store any types of data like structured, unstructured and semistructured
Data ishighly availableand accessible despite hardware failure due to multiple copies of data. If a machine or few hardware crashes, then data will be accessed from another path.
Hadoop works on data locality principle which states that move computation to data instead of data to computation. When a client submits theMapReducealgorithm, this algorithm is moved to data in the cluster rather than bringing data to the location where the algorithm is submitted and then processing it.
Easy to use
To get complete details of all the feature of Hadoop refer below link: