HBase and HDFS are two different types of data storage systems.
HDFS (Hadoop Distributed File System) is a distributed file system that stores data across multiple nodes in a cluster. It is designed to provide high throughput access to data stored in files, and is commonly used in conjunction with Hadoop for data processing and analytics.
HBase (Hadoop Database) is a distributed, column-oriented database that runs on top of HDFS. It is designed to provide real-time, random read/write access to data stored in HDFS. HBase is used for storing large amounts of unstructured data such as web logs, sensor data, and user profiles.
For example, if you are running a web application that needs to store and analyze user profiles, you could use HDFS to store the user profiles in files, and HBase to store the user profiles in a distributed database. HBase can then be used to perform real-time analytics on the user profiles, while HDFS can be used to store the data in a reliable and scalable way.