The Hadoop operating system is used to handle large amounts of data.
Optimized for parallel processing of structured and unstructured data while utilizing low-cost hardware.
Hadoop processing is batch-based rather than real-time, with data replication over the network and fault tolerance.
Hadoop is not a replacement for structured data in relational databases or online transactions. It can process unstructured data, which accounts for more than 80% of all data on the planet.
The 11 million pages and 4TB of data from the New York Times stories published between 1851 and 1922 were converted to a Hadoop cluster on Amazon's AWS for a reasonable cost, utilising a single employee who completed the work in under 24 hours.
Hadoop-based solutions, as well as other analytical applications, are useful, accessible, and quick to implement. For details, You can get a better understanding with the Hadoop big data course.