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Difference Between RDBMS and Hadoop
  • Last Updated : 22 May, 2020

RDMS (Relational Database Management System): RDBMS is an information management system, which is based on a data model.In RDBMS tables are used for information storage. Each row of the table represents a record and column represents an attribute of data. Organization of data and their manipulation processes are different in RDBMS from other databases. RDBMS ensures ACID (atomicity, consistency, integrity, durability) properties required for designing a database. The purpose of RDBMS is to store, manage, and retrieve data as quickly and reliably as possible.

Hadoop: It is an open-source software framework used for storing data and running applications on a group of commodity hardware. It has large storage capacity and high processing power. It can manage multiple concurrent processes at the same time. It is used in predictive analysis, data mining and machine learning. It can handle both structured and unstructured form of data. It is more flexible in storing, processing, and managing data than traditional RDBMS. Unlike traditional systems, Hadoop enables multiple analytical processes on the same data at the same time. It supports scalability very flexibly.

Below is a table of differences between Data Science and Data Visualization:

S.No. RDBMS Hadoop
1. Traditional row-column based databases, basically used for data storage, manipulation and retrieval. An open-source software used for storing data and running applications or processes concurrently.
2. In this structured data is mostly processed. In this both structured and unstructured data is processed.
3. It is best suited for OLTP environment. It is best suited for BIG data.
4. It is less scalable than Hadoop. It is highly scalable.
5. Data normalization is required in RDBMS. Data normalization is not required in Hadoop.
6. It stores transformed and aggregated data. It stores huge volume of data.
7. It has no latency in response. It has some latency in response.
8. The data schema of RDBMS is static type. The data schema of Hadoop is dynamic type.
9. High data integrity available. Low data integrity available than RDBMS.
10. Cost is applicable for licensed software. Free of cost, as it is an open source software.

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