Final answer:
HDFS, or Hadoop Distributed File System, is a distributed file storage system designed for scalably handling large data sets across multiple machines, offering high fault-tolerance on commodity hardware. It differs from traditional file systems in its design, offering redundancy and reliability through data replication, and its capability to manage petabytes of data, unlike traditional systems which are limited by single machine storage.
Step-by-step explanation:
What is HDFS?
Hadoop Distributed File System (HDFS) is a distributed file storage system designed to run on commodity hardware. It is a key component of Apache Hadoop, an open-source software framework used for distributed storage and processing of big data sets. HDFS is highly fault-tolerant and is designed to be deployed on low-cost hardware. It provides high throughput access to application data and is suitable for applications with large data sets.
How is HDFS different from traditional file systems?
The primary differences between HDFS and traditional file systems lie in their design, scalability, and fault tolerance. Unlike traditional file systems, which are designed for storage on a single machine, HDFS is designed for scalability across multiple machines, ensuring redundancy and reliability of data through data replication on multiple nodes. Traditional file systems are limited in their ability to handle very large datasets; HDFS, on the other hand, excels at storing and managing petabytes of data. Another key difference is the write-once-read-many approach of HDFS, which is optimized for batch processing, as opposed to the read-and-write capabilities of traditional file systems.