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Table of contents
1.
Introduction
2.
Storage Mechanism in HBase
3.
Features of HBase
4.
Applications of HBase
5.
HBase vs RDBMS
6.
FAQs
7.
Key Takeaways
Last Updated: Mar 27, 2024

HBase Introduction

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Introduction

In past decades generated data was structured and much lesser in amount than today. RDBMS was used to store these kinds of data. But Nowadays, we process a massive amount of semi-structured data like emails,JSONS,XML,.csv files, etc. RDBMS failed to store and manage this data, and HBase came into the picture.

HBase is a data model similar to Google's big table designed to provide quick random access to vast amounts of structured data. HBase is an open-source, multidimensional, distributed, scalable NoSQL database written in Java and runs on top of HDFS (Hadoop Distributed File System). It is designed to store a large collection of sparse data sets. It allows users to retrieve information instantly. 

For example, HBase quickly does this job if HBase contains 5 billion records and we wish to find 20 large items.

Also see, Multiple Granularity in DBMS

Storage Mechanism in HBase

HBase is a column-oriented database in which the data is stored in a table. In the HBase table schema, only column families are defined. The HBase table has multiple families, and each family can have unlimited columns. The column values are stored sequentially on a disk. Every table cell has its timestamp (which means a digital record of time or occurrence of a particular event at a future time.)

  • Table: The table is a collection of rows. 
  • Row: Row is a collection of column families.
  • Column family: It is a collection of columns. 
  • Column: A column is a group of key-value pairs.
  • Timestamp: It keeps a record of digital time and date. 
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Features of HBase

HBase has several features:

  1. Scalable: HBase allows data to be scaled across various nodes as it is stored in HDFS.
  2. Automatic failure support: Write ahead. Log across clusters are present that provide automatic support against failure.
  3. Consistent read and write: HBase provides consistent read and writes of data.
  4. JAVA API for client access: HBase provides an easy-to-use JAVA API.
  5. Block cache and Bloom filters: It supports block cache and bloom filters for high-volume query optimization.

Applications of HBase

  • Medical: In the medical industry, HBase stores the patient's data such as patient diseases, age, gender, etc., to run MapReduce on it.
  • Sports: In the Sports industry, HBase stores the information related to the matches. This information would help perform analytics and predict the outcomes in future matches. 
  • Web: The web uses HBase services to store the history searches of the customers. This search information helps the companies target the customer directly with the product or service they had looked for. 
  • Oil and petroleum: HBase is used to store the exploration data, which helps analyze and predict the areas where we can find oil.
  • E-commerce: E-commerce uses HBase to record the customer logs and the products they are searching for. It enables the organizations to target the customer with the ads to induce him to buy their products or services.       

HBase vs RDBMS

HBase RDBMS
HBase is schema-less. It doesn't have the concept of fixed columns schema; it 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 suitable for semi-structured as well as structured data. It is suitable for structured data.

FAQs

  1. Why should we use HBase in Apache?
    If we find that our data is stored in collections, such as some metadata, message data, or binary data that is all keyed on the same value, we should consider HBase. HBase should be considered if we need key-based access to data while storing or retrieving them.
     
  2. What is the difference between Hadoop and HBase?
    Hadoop and HBase are both used to store a massive amount of data. But the main difference is that in Hadoop Distributed File System (HDFS), data is stored in a distributed manner across different nodes in a network. Whereas HBase is a database that stores data in columns and rows in a Table.
     
  3. Why is HBase faster than RDBMS?
    Hbase follows the ACID Properties. HBase is a column-oriented database management system that runs on top of the Hadoop Distributed File System (HDFS). It is suitable for sparse data sets, common in many big data use cases.

Key Takeaways

We learned about HBase and the storage mechanism used in HBase.We also learned what the differences between HBase and RDMBS are. We get to know why HBase is needed even if RDBMS was present. We discovered about applications of Hbase in various fields around the globe.

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