Case Study : AWS relational database service for a leading transportation company


Case Studies


Wissen Team


August 16, 2023

Business Need:

Our client, a leading industrial conglomerate, depended on data extractions from Distinct source like Databases, Sensors, Files Systems, Events, and Logs needs to deal with multiple Data Handling Methods. Designing an Architecture with a specific Data Handling Capability, might not be an efficient way of Implementation. Capturing the data from a streaming process and storing the data in the easy extractable format might be a challenge.

Solution and Approach:

AWS Relational Database Service (RDS) provides Storage and Data Processing Medium for structured/Semi Structured data with very popular Query Engines Like PostgreSQL, Oracle, MySQL, Maria Db and Aurora DB. A key feature which made AWS RDS most popular is, it can connect from anywhere in the organization.

Designing an Architecture which includes AWS RDS as a core component, our client can capture the data from Files, APIs, Databases, and store in RDS. This approach has overcome the challenge of storing and retrieving the data to/from Multiple Storage Devices.

AWS RDS can be able to establish connection from anywhere within the organization. It requires only Client Software to Read/Write the data into AWS RDS. As it is a service provided by AWS, organizations were charged on for the resources used.

Now users can Read/Write the data directly into a Single database from multiple locations, applications, API and Databases with the approach discussed.


Amazon RDS is a managed service, which means it provides a high level of security for PostgreSQL databases. These include network isolation using Amazon Virtual Private Cloud (VPC)and private subnet, encryption keys created by the organization and control through AWS Key Management Service (KMS) and encryption of data in transit using SSL.

The automated backup feature of Amazon RDS enables recovery of database instance to any point in time within specified retention period defined by the organization. So, it is very useful in disaster recovery.

On a higher level of scope there is almost 45% increase in the Query performance from End-to-End and 18% lesser cost. Because of the backups enabled, data and platform are almost 100% available to use. With this approach Administration and User Management is reduced to more than 70%.