Describe the attributes of Hadoop.

Hadoop helps with both data storage and big data processing. It is the most dependable method for overcoming significant data obstacles. Some key characteristics of Hadoop include:

Distributed Processing: Hadoop facilitates distributed data processing, which results in faster processing. MapReduce is responsible for the parallel processing of the distributed data that is collected in Hadoop HDFS.

Open Source - Because Hadoop is an open-source framework, it is free to use. The source code may be modified to suit the needs of the user.

Fault Tolerance: Hadoop has a high level of fault tolerance. It makes three replicas at different nodes by default for each block. This replica count might be changed based on the situation. Therefore, if one of the nodes fails, we can retrieve the data from another node. Data restoration and node failure detection are done automatically.

Scalability: We can quickly reach the new device even though it has different hardware.



Reliability: Hadoop stores data in a cluster in a secure manner that is independent of the machine. So, any machine failures have no impact on the data saved in the Hadoop environment.