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Table of contents
1.
Introduction
2.
Columnar Database
3.
Hbase Columnar Database
4.
Characteristics
5.
Applications
6.
Frequently Asked Questions
7.
Conclusion
Last Updated: Mar 27, 2024
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Hbase Columnar Database in big data

Author Nagendra
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Introduction

In today's world of new technology, data plays a critical role in improving the nature of products and their reach to customers. Information is critical in assisting with this factor. Companies have begun to rely on assessments advanced by their internal processes, business operations, and customers to explore new chances for progress and success in the ever-changing international economy. Such insights present a huge, complex set of data that must be produced, maintained, examined, and manipulated. It is efficient to utilise a columnar database if you have a lot of data and it's diverse. It's incredibly customizable.

Columnar Database

The data in a columnar, or column-oriented database, is stored in rows, unlike the relational databases where data in each row of a table is kept together. Although this may appear to be a minor distinction, it is the most fundamental feature of columnar databases. It's simple to add columns, and you can do so row by row, giving you a lot of flexibility, performance, and scalability. In data warehouses, where corporations transfer huge amounts of data from many sources for BI analysis, columnar databases are used. Because the column design puts data closer, column-oriented databases have better query performance. This minimises seek time.
Column-oriented database table storage is critical for analytic query performance since it dramatically reduces total disc I/O requirements and the quantity of data you must load from the disc.

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Hbase Columnar Database

Hbase is a popular columnar database that relies on the Hadoop Distributed File System (HDFS) for data storage. It is a fault-tolerant storage system for sparse data sets, common in many big data applications. It's ideal for real-time data processing and random read/write access to massive data sets.HBase, unlike relational database systems, does not allow a structured query language such as SQL; in fact, HBase isn't even a relational data store. HBase apps, like Apache MapReduce applications, are written in JavaTM. HBase supports the Apache Avro, REST, and Thrift programming languages.
HBase is based on Google's BigTable (an efficient method of storing non-relational data). As a result, HBase implementations are multidimensional sorted maps that are very scalable, sparse, distributed, and durable. A row key, column key, and timestamp are used to index the map, and each value is an uninterpreted array of bytes. HBase is an excellent choice when your big data system necessitates random and real-time read/write data access. It is frequently used to save results for subsequent analysis. An HBase system is built to scale linearly. It is similar to a regular database in that it consists of a set of standard tables with rows and columns. A primary key must be set for each table, and all access attempts to HBase tables must use this primary key.

Characteristics

The following are the major characteristics of the Hbase Columnar Database:

  • Consistency
    HBase delivers strongly consistent reads and writes and is not based on an eventually consistent model, despite not being an "ACID" implementation. This means you can use it for high-speed needs as long as you don't require RDBMS' "additional features," such as full transaction support or typed columns.
  • Sharding:
    HBase allows transparent, automatic splitting and redistribution of its content because the data is delivered through the underlying file system.
  • High availability:
    HBase provides LAN and WAN failover and recovery using region servers. A master server is at the heart of the cluster, and it is responsible for monitoring the region servers and the cluster metadata.
  • Client API:
    HBase provides a Java API for programmatic access.
  • IT operations assistance:
    Through a set of built-in web pages, implementers can disclose the performance and other information.

Applications

The applications of the Hbase Columnar Database are :

  • Hbase is used for high volume gathering and processing of incremental data.
  • It is used for Real-time information exchange (for example, Voice over landlines and mobile phones, messaging) 
  • It is also used for serving Dynamic data.

Frequently Asked Questions

  1. What is Hbase?
    Hbase is a popular columnar database that relies on the Hadoop Distributed File System (HDFS) for data storage.
     
  2. What is a Columnar Database? 
    A columnar database is a type of database management system (DBMS) in which data is stored in columns rather than rows. A columnar database's goal is to reduce the time it takes to return a query by quickly writing and reading data to and from hard disc storage.
     
  3. How do columnar databases minimise seek time? 
    In a columnar database, the column design puts the data closer together, which has better query performance and minimises seek time.
     
  4. What are the main characteristics of the Hbase Columnar Database?
    The main characteristics of the Hbase Columnar Database are Consistency, Sharding, High availability, Client API, and IT operations assistance.

Conclusion

In this article, we have extensively discussed Hbase Columnar Database in big data. The article explains the details of the Hbase Columnar Database, its characteristics, and its applications.
We hope that this blog has helped you enhance your knowledge regarding Hbase Columnar Database in big data and if you would like to learn more, check out our articles on big dataHadoopMongoDBDatabases for development, and SQL vs. NoSQL. To practice and improve yourself in the interview, you can check out Top 100 SQL problemsInterview experienceCoding interview questions, and the Ultimate guide path for interviews.
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