A Traditional Relational Database Schema Showing Tables and Relations

A Traditional Relational Database Schema Showing Tables, Relations, & Keys


A relational database management system (RDBMS) is a database management system (DBMS) that is based on the relational model.

In 1970, Edgar F. Codd, a British computer scientist with IBM, published “A Relational Model of Data for Large Shared Data Banks.” At the time, the renowned paper attracted little interest, and few understood how Codd’s groundbreaking work would define the basic rules for relational data storage for decades to come, which can be simplified as:

  1. Data must be stored and presented as relations, i.e., tables that have relationships with each other, e.g., primary/foreign keys.
  2. To manipulate the data stored in tables, a system should provide relational operators – code that enables the relationship to be tested between two entities. A good example is the WHERE clause of a SELECT statement, i.e., the SQL statement SELECT * FROM CUSTOMER_MASTER WHERE CUSTOMER_SURNAME = ’Smith’ will query the CUSTOMER_MASTER table and return all customers with a surname of Smith.

RDBMSs have been a common choice for the storage of information in databases used for financial records, manufacturing and logistical information, personnel data, and other applications using historical, transactional data since the 1980s.

However, relational databases have received unsuccessful challenge attempts by object database management systems in the 1980s and 1990s (which were introduced trying to address the so-called object-relational impedance mismatch between relational databases and object-oriented application programs) and also by XML database management systems in the 1990s.

Despite such attempts, RDBMSs keep most of the market share, but that share is declining because of the lack of the ability to scale, concurrency issues, and the high network bandwidth required for queries having to traverse many tables that have been architected to be highly normalized. Database normalization is the technique used in organizing the data in an RDBMS. It’s a systematic approach of decomposing tables to eliminate data redundancy and improve data integrity.

Two examples of traditional relational databases are Microsoft SQL Server & Oracle Databases.

In Chapter 22, the second section will compare traditional relational databases with Amazon RDS Aurora database, that is a new RDBMS built from the ground up for the cloud and just recently surpassed Amazon Redshift to be AWS’ fastest growing service.

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This entry was posted in Amazon Aurora, Amazon Web Services, AWS BI, Microsoft SQL Server, Oracle Database, RDBMS, Traditional Relational Database Systems. Bookmark the permalink.

1 Response to TRADITIONAL RELATIONAL DATABASE MANAGEMENT SYSTEMS (Chapter 3.6 in “All AWS Data Analytics Services”)

  1. Nice Information about data management service MRU consulting from the same field who provide the data management services


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