Relational Database
Relational Database Is:
Program-data independence
Planned data redundancy
Improved data consistency
Improved data sharing
Increased productivity of application development
Improved data quality
Reduced program maintenance
Eliminate data anomalies by following normalization techniques
Unlike flat file data stores, RDBMS are designed to use a common language called SQL to manipulate data.
Applications of Relational Database
Relational databases still widely used for structured data
Object-oriented, object-relational, and NoSQL databases are also extensively used as the growth in unstructured content
Somewhat fueled by Web 2.0 applications
Create unstructured data such as pictures, images, and videos
Amazon, Alphabet (Google), Microsoft, Meta (Facebook), Apple, and Netflix support large numbers of users on the Web
Needed to support
Large volumes of read and write operations
Low latency and response times
High availability
Limitations Of Relational Database
Web applications serving tens of thousands or more concurrent users were difficult to implement with RDB
To improve scalability: need powerful servers, multiple server for RDB
To handle complexity: If the data doesn’t fit into tables, need to design database structure that will be complex and again difficult to handle
Because of data in terms of
Volume, Velocity, Variety, Veracity, Value
Unstructured, semi-structured
Real-time live streaming data
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