AWS Relational Database Services Overview | Generated by AI

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Relational Databases on AWS

AWS provides several managed services for relational databases, with Amazon Relational Database Service (RDS) being the primary offering. It handles setup, patching, backups, and scaling for various popular database engines. Additionally, Amazon Aurora is a high-performance, MySQL- and PostgreSQL-compatible relational database built into RDS.

Here’s a summary of the key relational database options on AWS:

Service/Engine Description Use Cases
Amazon RDS for PostgreSQL Fully managed PostgreSQL, supporting advanced features like JSONB and full-text search. Transactional applications, web apps, and analytics.
Amazon RDS for MySQL Managed MySQL with high availability and read replicas. E-commerce, content management, and general-purpose apps.
Amazon RDS for MariaDB Fork of MySQL with enhanced performance and storage engines. Web applications and read-heavy workloads.
Amazon RDS for SQL Server Microsoft SQL Server with editions like Standard, Enterprise, and Web. Enterprise apps, BI, and Windows-based systems.
Amazon RDS for Oracle Oracle Database with BYOL (Bring Your Own License) or license-included options. Mission-critical enterprise applications.
Amazon RDS for Db2 IBM Db2 with support for LUW (Linux, UNIX, Windows). Large-scale transactional and analytical workloads.
Amazon Aurora (MySQL-compatible) Cloud-native relational DB with up to 5x faster performance than standard MySQL. High-throughput OLTP and global apps.
Amazon Aurora (PostgreSQL-compatible) PostgreSQL-compatible with serverless options and auto-scaling storage. Scalable apps requiring ACID compliance and high availability.

For data warehousing (OLAP-focused relational workloads), AWS also offers Amazon Redshift, a fully managed, petabyte-scale data warehouse based on PostgreSQL.

These services integrate seamlessly with other AWS tools like EC2, Lambda, and S3. To get started, check the AWS RDS documentation or AWS Database Services overview.


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