Vijay Kumari
What are the basic differences between relational database and HDFS?
By Vijay Kumari in Big Data on Jul 22 2019
  • Elavarasan R
    Aug, 2019 16


    • It is available to process Structured, unstructured and semi-structured data.
    • Open source no cost for the license.
    • Support read and write many times.
    • It works well in Big Data processing.


    • It performs to function only in structured data.
    • Cost is applicable for License.
    • Write once and read many times.
    • It works well in Online transaction Processing.-

    • 1
  • Laxmidhar Sahoo
    Jan, 2020 2


    Hadoop File System(HDFS) was developed using distributed file system design. It is run on commodity hardware. Unlike other distributed systems, HDFS is highly faulttolerant and designed using low-cost hardware.

    HDFS holds very large amount of data and provides easier access. To store such huge data, the files are stored across multiple machines. These files are stored in redundant fashion to rescue the system from possible data losses in case of failure. HDFS also makes applications available to parallel processing.

    Features of HDFS
    It is suitable for the distributed storage and processing.
    Hadoop provides a command interface to interact with HDFS.
    The built-in servers of namenode and datanode help users to easily check the status of cluster.
    Streaming access to file system data.
    HDFS provides file permissions and authentication.


    RDBMS is relational database management system. Database management system (DBMS) stores data in the form of tables, which comprises of columns and rows. The structured query language (SQL) will be used to extract necessary data stored in these tables. The RDBMS which stores the relationships between these tables in different forms such as one column entries of a table will serve as a reference for another table. These column values are known as primary keys and foreign keys. These keys will be used to reference the other tables so that the appropriate data can be related and be retrieved by joining these different tables using SQL queries as needed. The tables and the relationships can be manipulated by joining appropriate tables through SQL queries.

    ACID Property
    With SQL, you will get the support of RDBMS ACID properties – Atomicity, Consistency, Isolation, and Durability. However, in Hadoop, this is not out of the box. So you have to code all the scenarios to implement commit or rollback during a transaction.

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