HBase Overview#

Why HBase#

  • RDBMS get exponentially slow as the data becomes large

  • Expects data to be highly structured, i.e. ability to fit in a well-defined schema

  • Any change in schema might require a downtime

  • For sparse datasets, too much of overhead of maintaining NULL values

HBase Data Model#


HBase Commands#

  • Create: Creates a new table identified by ‘table1’ and Column Family identified by ‘colf’.

  • Put: Inserts a new record into the table with row identified by ‘row..’

  • Scan: returns the data stored in table

  • Get: Returns the records matching the row identifier provided in the table

  • Help: Get a list of commands

HBase and HDFS#

HDFS is a distributed file system suitable for storing large files. HBase is a database built on top of the HDFS.
HDFS does not support fast individual record lookups. HBase provides fast lookups for larger tables.
It provides high latency batch processing; no concept of batch processing. It provides low latency access to single rows from billions of records (Random access).
It provides only sequential access of data. HBase internally uses Hash tables and provides random access, and it stores the data in indexed HDFS files for faster lookups.

HBase and RDBMS#

HBase is schema-less, it doesn't have the concept of fixed columns schema; defines only column families. An RDBMS is governed by its schema, which describes the whole structure of tables.
It is built for wide tables. HBase is horizontally scalable. It is thin and built for small tables. Hard to scale.
No transactions are there in HBase. RDBMS is transactional.
It has de-normalized data. It will have normalized data.
It is good for semi-structured as well as structured data. It is good for structured data.