Data Management Technologies: SQL, Hadoop, and HBase Comparison

This report provides a comparative analysis of SQL, Hadoop, and HBase technologies, focusing on their advantages in data management and query answering. The report highlights the benefits of SQL, such as streamlined installation, robust security features, cost-effectiveness, ease of use, and support for multiple data views. It also discusses Hadoop's scalability, cost-effectiveness, flexibility, and speed in processing large datasets. Additionally, the report explores HBase's suitability for random read/write operations, its ability to handle large datasets, and its efficient data processing capabilities. The report includes examples to illustrate each advantage, making it a comprehensive overview of these database technologies.

Database Management Technologies 1
DATABASE MANAGEMENT TECHNOLOGIES
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Technology Advantage
SQL:  Installation is streamlined: Example SQL technology can be
streamlined through a set-up wizard
 SQL technology offers great security features: The technology
uses what database administrator refer to as policy-based
management feature to detect database security policies
 Low cost of ownership: TSQL technology includes data mining
tools and an effective data management along with disk
partitioning
 Follows the least privilege principle
 No coding: Very easy to manage. Example it does not require
substantial amount of code to management the database
 Multiple data view: Example one can view data in form of
integers, strings, and flout
 Interactive language: Example SQL is communicating to
everyone (Hoffer, et al., 2016, p. 37)
Hadoop  Scalable: Example hadoop can distribute and store large amount
of data sets
 Cost effective: It explodes other data sets.
 Flexible: Example it enables an organization to easily access
new data sources. It derives an organization insights from
various data sources like email conversations, clickstream data,
or social media.
 Fast: Example, the tools of processing are on the same database
servers where information or data is located.
Hbase  Widely used example on online analytical operations
 Used for Random write and read operations example in ATM
applications
 With Hbase database can be shared example is online
transactions
 Hbase has the ability of storing large data sets example it
analyses billions of rows present in the Hbase tables
 Takes very limited time to process operations example are the
data reading operations and data processing which takes very
small amount of time as compared to the normal traditional
relational models
 Schema-less: Example there is no fixed columns schema In
HBase technology as it defines column families only
 Easy to use Java API for user client access: It offers easy usage
Java API (Erickson, 2015, p. 79)

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References
Erickson, o., 2015. Database technologies : concepts, methodologies, tools, and applications.
2nd ed. Chicago: John & wiley.

Database Management Technologies 4
Hoffer, J. A., Ramesh, V. & Topi, H., 2016. Database management. 1st ed. Boston: Pearson
Education Press.