Databases on AWS: Key Strategies and Approaches

Databases on AWS: Key Strategies and Approaches

Amazon Web Services (AWS) is a leading cloud provider that offers a wide range of computing, storage, and machine learning services. In this article, we will take a look at AWS services and determine the best strategies for choosing a database according to business needs.

Types of databases

Relational databases vs. NoSQL

A relational database (RDBMS) is a database organized in the form of tables with linked rows and columns. RDBMS uses SQL and allows you to manage and store large amounts of data in a structured way.

NoSQL is a database for storing and managing unstructured or semi-structured data. It does not use tables, and this differs it from relational databases. The flexibility and scalability of NoSQL allows you to process large amounts of data and get quick access to it.

AWS database services

AWS RDS (Relational Database Service)

This web service allows you to create, configure and manage relational databases in a cloud environment. AWS RDS supports MySQL, PostgreSQL, Oracle, SQL Server and Amazon Aurora. The service automatically runs backups, scales data and monitors performance.

Amazon DynamoDB

DynamoDB uses the NoSQL model to store and organize data. This service is used to work with large amounts of data in real time. DynamoDB manages all aspects of the database infrastructure and allows you to create fast, scalable applications in the AWS environment.

Amazon Redshift

Cloud service for data storage, analytics, and reporting. It automatically manages data distribution and replication. Redshift supports standard SQL to execute queries and integrates with other AWS services.

Amazon Aurora

A relational database that supports MySQL and PostgreSQL. It has built-in automatic scaling, backup and recovery features. Amazon Aurora provides high query processing speed for working with large amounts of data.

Choosing a database

Needs of the project

Choosing a database involves analyzing various aspects: data volume and types, performance, scalability, integration with other systems, etc. In this process, you need to study the requirements, functionalities and user needs.

For example, if a project requires quick access to structured data with complex relationships, a relational database may be a better choice. At the same time, if the data is flexible and scalable, a NoSQL database is more suitable.

Business requirements

An important aspect of choosing a database is adapting the system to specific needs and goals. For example, if a business needs to store and process confidential information, the choice of a database should be based on encryption and access control capabilities.

It is also important to pay attention to the scalability and reliability of the system, as the business may grow and develop over time. Meeting business requirements ensures effective data management and helps the company achieve its strategic goals.

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