HBase vs RDBMS: Feature Wise Comparison
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1. HBase vs RDBMS
Today, in this article “HBase vs RDBMS: Feature Wise Comparison” we will learn the complete comparison of HBase vs RDBMS, on the basis of several features. Both HDFS and RDBMS are varying concepts of processing, retrieving and storing the data or information. Still, there are some reasons that HBase has lacks comparison to conventional relational databases which are even existed for so long now.
So, let’s begin HBase vs RDBMS
2. Difference Between HBase & RDBMS
i. What is HBase?
An open source and sorted map data built on Hadoop is what we call HBase. Basically, it is column-oriented and horizontally scalable. Moreover, it offers APIs enabling development in practically any programming language. Also, it offers random real-time read/write access to data in the Hadoop File System, as it is a part of the Hadoop ecosystem that.
Follow the link to learn more about HBase
ii. What is RDBMS?
RDBMS refers to Relational Database Management Systems. Basically, systems like SQL, MS SQL Server, IBM DB2, Oracle, MySQL, and Microsoft Access are based on RDBMS. Since it is based on the relational model introduced by E.F. Codd so it is called Relational Database Management System (RDBMS).
If these professionals can make a switch to Big Data, so can you:
3. Feature Wise Comparison of HBase vs RDBMS
Below we are discussing the feature wise difference of HBase vs RDBMS, let’s explore this in detail:
i. Database Type
HBase is the column-oriented database. On defining Column-oriented, each column is a contiguous unit of page.
Whereas, RDBMS is row-oriented that means here each row is a contiguous unit of page.
Schema of HBase is less restrictive, adding columns on the fly is possible.
However, Schema of RDBMS is more restrictive.
iii. Sparse Tables
HBase is good with the Sparse table.
Whereas, RDBMS is not optimized for sparse tables.
Read HBase Operations: Read and Write Operations
iv. Scale up/ Scale out
HBase supports scale out. It means while we need memory processing power and more disk, we need to add new servers to the cluster rather than upgrading the present one.
However, RDBMS supports scale up. That means while we need memory processing power and more disk, we need upgrade same server to a more powerful server, rather than adding new servers.
v. Amount of data
While here it does not depend on the particular machine but the number of machines.
In RDBMS, on the configuration of the server, amount of data depends.
vi. Support of
For HBase, there is no built-in support.
And, RDBMS has ACID support.
vii. Data type
HBase supports both structured and nonstructural data.
RDBMS is suited for structured data.
viii. Transaction integrity
In HBase, there is no transaction guaranty.
Whereas, RDBMS mostly guarantees transaction integrity.
Let’s explore HBase Pros and Cons | Problems with HBase
HBase supports JOINs.
RDBMS does not support JOINs.
x. Referential integrity
While it comes to referential integrity, there is no in-built support.
And, RDBMS, supports referential integrity.
4. Features of HBase and RDBMS
- Why HBase?
- HBase is horizontally scalable.
- Integrations with Map/Reduce framework.
- Moreover, it is possible to refer HBase as a key-value store or column family-oriented database.
- Why RDBMS?
- Here, in form of rows and columns, data stores.
- By using SQL queries, it also supports virtual tables from where we can retrieve data.
- For the purpose of data uniqueness, RDBMS provides a primary key.
- Also, it offers referential integrity.
Hence, in this HBase tutorial, we saw the difference between HBase & RDBMS. Moreover, we have seen the complete comparison and the features of HBase and RDBMS. However, if any doubt occurs regarding HBase vs RDBMS, feel free to ask in the comment section.
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