A technology that has emerged as the frontrunner for handling Big Data processing is Hadoop. This efficient platform aids in storing, handling and retrieving enormous amounts of data in a variety of applications while also helping in deep analytics. As more and more companies are embracing Hadoop, the demand for Hadoop Developers is growing.
Features of Big Data Hadoop
- Economic – Hadoop is not very expensive as it runs on the cluster of commodity hardware. we don’t need to spend a huge amount of money for scaling out your Hadoop cluster As we are using low-cost commodity hardware
- Data Locality – Instead of moving data to computation, learn more about data locality. It refers to the ability to move the computation close to where actual data resides on the node. This minimizes network congestion and increases the over throughput of the system.
- Scalability – Hadoop provides horizontal scalability so new node added on the fly model to the system. This makes it extremely scalable platform. So, new nodes can be easily added without any downtime. In Apache hadoop, applications run on more than thousands of node. Hadoop is an open-source platform
- Distributed Processing – Hadoop stores huge amount of data in a distributed manner in HDFS. It process the data in parallel on a cluster of nodes.