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Introduction to Apache HBase

Hadoop, Data Science, Statistics & others

How does Apache HBase Works?

Apache HBase is a data model that stores the semi-structured form of data with a different kind of data type with dynamic field size and varying column size. There are several logical components present inside the Hbase data model. Those include the row key, table name, column family, timestamp, etc. As the name suggests, the row key is specifically used to provide and identify the rows in HBase tables. The column families in the case of HBase are static, whereas columns are termed as dynamic in nature.

What is the Use of Apache HBase?

Apache HBase’s applications include many sectors wherever the need arises to handle large amounts of data, and the use of a NoSQL database is required.

Let us discuss some of the applications of Apache HBase:

1. Medical Field

HBase is used widely in medicine as it can be used to store genome sequences. It also runs MapReduce on top of it. Therefore, it can also hold the history of people with chronic or non-chronic diseases that could be based on geographic or non-geographic region.

2. Web and Internet 3. Sports

In sports, be it any sport, HBase serves the primary purpose of storing the players’ historical data. By looking at this, the match forecast can be predicted along with the type of gameplay by the particular team.

4. E-Commerce

The E-commerce market has gained much popularity with every passing day, and more business means more data. Therefore huge stock-keeping inventories are needed to be maintained for the high level of PSKUs and SKUs which are being shipped and for maintaining a track record of all the inventory present. Also, customer preferences and choices are considered, and huge data is easily stored in HBase.

5. Oil and Petroleum

HBase is also widely used in the petroleum, gas, and oil industry. It is used to store the exploration data that can be used for analysis and predict the probability of the prices surge along with the rigs and shores for where the oils can be found.

6. Banks and Other Financial Institutions

Banks and other financial institutions related to the credit card industry or core financial banking also need to store customers’ crucial data, which becomes high in volume. Therefore, HBase comes into play.

Advantages of Using HBase

It is a great tool for analytics, along with the usage of Hadoop MapReduce

It is used to support scaling and the coordination of the Hadoop file system, which can be done even on the commodity hardware.

It is used to handle large volumes of data.



It is flexible when you talk about schema design.

Multiple integrations such as with Hive for SQL-like queries.

Auto failover.

Auto sharding.

Simple client-side interface.

Row-level of atomicity.

Why should we Use Apache HBase?

It features in-memory techniques and operations like compression and bloom filters applied on a per column basis. The HBase tables serve the purpose of both the input and output for MR jobs. It can also be accessed by using Java API along with Avro, REST or thrift gateway-based APIs. Whenever your data is column-specific, going for HBase would not be a wrong solution as it also has a broad lineage. Furthermore, it runs on top of HDFS and therefore is faster in processing for reading and write operations which could be done for high throughput and low output latency.

How will this Technology help you in your Career Growth?

This technology becomes a major part of the Big data ecosystem, and as you are well aware that all the technologies related to big data have a huge scope. Moreover, HBase talks about handling and storing massive data, so a special kind of category of databases known as NoSql databases is designed to help organizations and businesses foster, and HBase form a key integral component in it.

Learning Apache HBase is always the right decision. It helps provide you with many insights about the usage and handling of a high volume of data efficiently and is also highly in demand in the market today.

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