Discovering Types of AWS Databases: Finding the Perfect Fit for Your Business

Have you ever wondered how the digital world functions smoothly despite the constant clicks and swipes? Let me introduce you to AWS, the backstage hero who makes sense of it all! AWS offers custom databases for businesses that aim to achieve big in the tech world. Every AWS database is different from each other, and they bring magic to help businesses shine in the digital world. So, let’s go over the types of AWS databases.

Types of AWS Databases

AWS provides a wide selection of database services from which to choose. It includes both relational and non-relational databases. We will see a brief description of all types of AWS databases. Each AWS database service has distinct benefits.

  • AWS Relational Database –  Amazon RDS, Amazon Aurora, Amazon Redshift
  • AWS Key-value Database – Amazon DynamoDB
  • AWS In-memory Database – Amazon ElastiCache, Amazon MemoryDB for Redis
  • AWS Document Database – Amazon DocumentDB
  • AWS Wide Column Database – Amazon Keyspaces
  • AWS Graph Database – Amazon Neptune
  • AWS Time Series Database – Amazon Timestream
  • AWS Ledger Database – Amazon Ledger Database Service

Most Used Types of AWS Databases

Now that you have clarity on all types of databases in AWS. Let’s look at the most popular types of AWS databases.

  • AWS RDS

AWS RDS is among the most popular types of AWS databases. It covers a variety of open-source relational database solutions. Amazon RDS also includes Amazon’s own database services. It is used to establish, manage, and grow a relational database. It automates hardware supply, database configuration, backups, and other management operations.

Features:

AWS RDS supports MySQL, PostgreSQL, and Microsoft SQL Servers.

It automates database management operations.

It has scalability options for performance enhancement.

Use Cases:

AWS RDS is suited for apps that require a relational database structure.

It is well-suited for scenarios demanding managed database services with minimal administrative overhead.

  • Amazon Aurora

It is an AWS-provided relational database engine. It suits each MySQL and PostgreSQL database and beats all commercial databases in performance. It has an operational efficiency of up to 5 times that of MySQL and 3 times that of PostgreSQL.

Features:

Amazon Aurora is developed for high performance, availability, and durability.

It is supported with MySQL and PostgreSQL.

Use Cases:

Amazon Aurora is critical for applications with high-performance demands.

It is suited for businesses seeking the benefits of both MySQL and PostgreSQL compatibility.

  • Amazon Redshift

Amazon Redshift is another database service from types of AWS databases with very high speed. It makes the process easier and speeds up data analysis using your current business intelligence tools. This service lets you easily execute complicated analytical queries on structured data. You will get the most answers in seconds. It can be used on a dedicated instance or on an as-needed basis.

Features:

It is developed for powerful performance analysis using SQL queries.

Amazon Redshift has massive parallel processing for quick data recovery.

Use Cases:

Amazon Redshift is perfect for analytical operations, complex queries, and large datasets.

It is suited for businesses that require scalable data warehousing solutions.

  • Amazon DynamoDB

Amazon DynamoDB is a completely automated database service. It is NoSQL, so it eliminates the requirement to write queries to extract data. Rather, you can perform these activities with a few mouse clicks, resulting in an interactive database with limitless features. It is a Key-value database that is capable of handling read and write requests rapidly.

Features:

Amazon DynamoDB supports document and key-value data models.

It has high performance and scalability with low-latency access.

Use Cases:

Amazon DynamoDB is excellent for applications with variable and unpredictable workloads.

It is ideal for scenarios requiring seamless scalability and low-latency data access.

  • Amazon ElastiCache

Amazon ElastiCache is an in-memory data storage type from types of AWS databases. It streamlines the handling and monitoring of in-memory infrastructure, resulting in shorter load times and improved user performance. ElastiCache offers a foundation for rapid data retrieval without depending on physical databases by utilizing an in-memory architecture. ElastiCache is an affordable and speedier alternative to typical data retrieval approaches for frequently used data.

Features:

Amazon ElastiCatch supports many other popular caching engines.

It is an in-memory caching service.

Use Cases:

Amazon ElastiCatch is ideal for scenarios requiring low-latency access to cached information.

It improves the Web app’s speed by caching often-used data.

  • Amazon Neptune

Amazon Neptune is a strong database service from all types of aws databases that can hold massive volumes of relationship data while providing speedy access. It stores connected data in a graph structure formatted by vertices and edges. It’s a fantastic solution for applications that demand extensive interconnected data sets. Neptune is also suitable for a variety of graph models. This makes it a flexible tool for developing and running applications that require enormous quantities of relationship data to be stored while ensuring low-latency access.

Features:

It is a graph database service.

Amazon Neptune supports both property and RDF graph models.

Use Cases:

Amazon Neptune is essential for applications dealing with highly connected data.

It is appropriate for situations in which interactions between data entities are critical.

Conclusion

AWS provides various database services to meet the needs of various businesses. This adaptability allows businesses to concentrate on innovation and development. It is critical to undertake comprehensive research about the different types of AWS databases. You can also get guidance from AWS migration services when picking a project’s proper AWS database type.


Author Bio: Chandresh Patel is a CEO, Agile coach, and founder of Bacancy Technology. His truly entrepreneurial spirit, skilful expertise, and extensive knowledge in Agile software development services have helped the organization to achieve new heights of success. Chandresh is fronting the organization into global markets systematically, innovatively, and collaboratively to fulfill custom software development needs and provide optimum quality.