How does HBase store and record data?

HBase is a distributed, high-performance, column-oriented NoSQL database that stores data on the HDFS file system of Hadoop. It organizes and manages data in tables, with each table consisting of multiple rows, each with a unique row key.

In HBase, the process of storing data records is as follows:

1. To create a table: Begin by using the HBase API to define a table. Specify details such as the table name and column families.
2. Inserting data: Use the Put operation to insert data into the table. Each Put operation requires specifying a row key, and then you can add data for multiple column families and columns.
3. Updating Data: Data can also be updated using a Put operation. If the row key already exists, it will update the values of the corresponding column family and columns. If the row key does not exist, it will insert a new record.
4. Retrieve data: Use the Get operation to query data. The Get operation requires specifying a row key and can choose to retrieve data from specific column families and columns.
5. Delete data: Use the Delete operation to remove data. The Delete operation requires specifying the row key and the option to choose which column family and column data to delete.
6. Batch processing: HBase also supports batch operations, allowing multiple data entries to be inserted or deleted at once, thus improving the efficiency of data operations.

It is important to note that HBase is a distributed database where data is automatically distributed across multiple Region Servers for storage. Each Region Server is responsible for managing a portion of the data for a particular table. During the data storage process, HBase automatically splits data based on row key ranges and assigns the split data to different Region Servers for storage. This allows for horizontal scaling and load balancing of the data.