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What is a Relational Database Management System? 

Relational database management systems (RDBMS) provide capabilities for creating and updating relational databases. RDBMS tools are typically based on structured query language (SQL), which is similar to English and is relatively easy to learn and use.  

Different RDBMS systems may use different variants of SQL. Some systems provide full support of all SQL commands, while others provide only a subset of commands needed for a specialized use case. 

RDBMSs have advanced greatly over the past 20 years. Today, many providers offer databases as a managed cloud service, with automated scaling and clustering. For example, learn about modern database systems offered on Amazon Web Services or Oracle database in the cloud. 

 

In this article, you will learn: 

  • Relational vs Non-Relational Databases 
  • RDBMS vs DBMS 
  • How Does an RDBMS Work? 
  • Top Relational Database Management Systems 
  • MySQL 
  • PostgreSQL
  • Oracle Database 
  • SQLite 

 

Relational vs Non-Relational Databases 

Non-relational databases (also known as NoSQL databases) do not use tabular relationships and provide different mechanisms for storing and retrieving data in the database.  

The main limitation of relational databases is that each item only has one representation in the database. For example, each aspect of a customer-company relationship (customer name, address, items purchased, invoice amounts, etc.), is stored as a separate row item in a separate table. All of these tables are linked together using a “primary key”.   

This structure enables efficient data retrieval and is very easy to query, however it can become very slow as data volumes and throughput increases.  

 In non-relational databases, key-value pairs allow multiple related items of data to be stored in a single data element. All data related to the customer can be stored in a single record. Data can be organized in a way that is
convenient for the application using and retrieving the data. This makes it possible to achieve very high performance, even for huge data volumes. On the other hand, it limits the ability to organize and query the data. 
 

 

RDBMS vs DBMS

Relational database management systems (RDBMS) are an advanced version of database management systems (DBMS). Here are some of the key differences between RDBMS and DBMS. 

 

  DBMS  RDBMS 
Concurrency  One user at a time  Uses algorithms that allow multiple users to access the database while maintaining data integrity 
Hardware resources  Uses fewer resources to store and retrieve data due to its simpler structure  Requires more hardware resources due to its multi-table structure and cross-reference functionality 
Data volume  Mainly suitable for smaller data volumes  Can handle large data volumes 
Keys and Indexes  Does not use keys and indexes  Uses keys and indexes to specify relationships between data elements, enabling faster data access 
Data consistency  Does not comply with the ACID (Atomic, Consistent, Isolation, and Durability) model  Complies with ACID model 
Structure  Stores data in a hierarchical structure  Stores data in tables 
Fetching speed  Fetching is slow, and becomes slower as the database grows  The relational approach and the use of SQL language results in faster data retrieval 
Distributed databases  No support  Full support for distributed database, sharding and clustering 
Client server  No support  Support for client server architecture.  

 

How Does an RDBMS Work? 

Relational database data structures use multiple tables arranged into rows, which are also called records, and columns, also called data fields. Relational database tables can be linked in a variety of ways, including: 

 

  • 1-to-1 relationship—a link between a record from one table with another record from a different table. 
  • 1-to-many relationship—records from one table can be linked with multiple records from a different table. 
  • Many-to-many relationship—multiple table records can be linked to multiple records in a different table. 

 

Each RDBMS table must satisfy these conditions: 

 

  1. The table has no null values, and no blank columns containing null values. 
  1. Each table has its own “primary key” which can be used to connect the table to other tables. 
  1. Each “foreign key” used to link two tables is stored in one table and references the primary key of another table. 

 

RDBMSs usually come with data dictionaries and metadata collections to aid in data management, user access and permission management. For example, each data table might have meta data indicating which users are allowed to read, write, or delete it.

 

Top Relational Database Management Systems

Below is a brief overview of popular RDBMSs. 
 

SQLite

SQLite is a widely used open source SQL database. You can store the entire database in one file. One of the most important benefits of this feature is that you can store all your data locally without having to connect the database to the server.  

Advantages: SQLite is commonly used for applications running on mobile phones, PDAs, set-top boxes and other electronic products or embedded systems.  

Downsides: Provides limited functionality and works with a subset of the SQL language. Poor performance with multiple users.  
 

Raima Database Manager (RDM)

RDM is a compact database developed for IoT edge devices. Like SQLite you can embed it inside of your application. RDM is designed to deliver consistent and dependable transactions per second while being multi-user friendly and efficient. 

Advantages: Lightweight (350k footprint), reliable and high performance.  

Downsides: Does not have all the bells and whistles of an enterprise database. 
 

MySQL
MySQL is a highly popular open source database based on SQL. The most common use case for MySQL is web software development. It is often accessed via PHP. 

Advantages: Easy to use, reliable, cost-effective, and supported by a large and active community. 

Downsides: Can experience performance degradation during scaling. Open source development has been slower since Oracle took control of MySQL. There are advanced features some developers may not be familiar with.
 

PostgreSQL

PostgreSQL is a free open source SQL database. It is growing in popularity and increasingly used for big data scenarios. 

Advantages: Easy to use, reliable, cost-effective, and supported by many developers. Additionally, PostgreSQL offers unique features like easy-to-configure foreign key support, and can support very large data volumes.  

Downsides: Performance is slower than other databases like MySQL. While PostgreSQL is less used than MySQL, it is rapidly gaining more popularity. 

 

Oracle Database 

A commercial offering by Oracle Corporation, which pioneered the modern RDBMS. 

Advantages: Oracle Database is particularly suitable for large-scale enterprise applications. It offers pre-integrated business applications and technologies, with a special focus on the financial industry.  

Downsides: Expensive, requires significant hardware resources to run, can be complex to deploy, configure and scale.
 

Raima Relational Database Management System

Raima Database Manager (RDM), is a linkable library that you easily embed within your application to Collect, Store, Manage and Move data in near real-time – requiring zero ongoing administration.  RDM is perfectly designed to be bundled inside applications that run on small embedded IoT or IIoT devices out on the edge or in the fog, e.g. collecting all information gathered from a network of sensors and actuators, then securely delivery that data up to enterprise level hardware systems in the Cloud. 

RDM comes fully compiled and packaged for software developers with options to meet a variety of data management architectural designs by providing a choice of data models and access methods to solve the most stringent performance requirements.  RDM is a solid time-tested ACID compliant database technology that employs a number of advanced options to meet today’s more complex data management challenges such as building highly-available database systems, moving data from small low-powered embedded devices up into larger enterprise systems, managing information purely in-memory, database partitioning support to facilitate data distribution and scalability, and interfaces allowing access to the data from external sources. 

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