In-Memory Databases vs. Relational Databases: Key Advantages and Use Cases

Aditya Bhuyan
8 min readNov 9, 2024

Introduction

In recent years, in-memory databases, often known as IMDbs, have gained substantial popularity as a result of the growing need among enterprises for data management solutions that are more scalable, more responsive, and faster. In contrast to conventional relational database management systems (RDBMS), which are dependent on disk storage, in-memory databases keep all of their data in random-access memory (RAM), which enables these databases to handle data more quickly. In-memory databases are the go-to solution for use cases that require extremely low latency, high throughput, and real-time analytics because of this shift in architecture, which offers a variety of benefits that make them an attractive option.

The advantages of using in-memory databases as opposed to relational databases are discussed in this article. Specifically, the paper investigates how in-memory databases outperform traditional systems under certain situations. During this discussion, we will delve into topics such as performance, scalability, use cases, and the restrictions that commercial enterprises ought to take into consideration while selecting between these two categories of databases. If you are thinking about switching to an in-memory database or if you simply want to gain a better understanding of…

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Aditya Bhuyan
Aditya Bhuyan

Written by Aditya Bhuyan

I am Aditya. I work as a cloud native specialist and consultant. In addition to being an architect and SRE specialist, I work as a cloud engineer and developer.

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