Amazon Aurora Vs Amazon RDS Comparison: Which is the Best Database Service?

Databases are the main pillars of any application and are one of the most essential business infrastructure components. Additionally, database management services have become vital not only in on-premises but also in the cloud platform.

Database-as-a-service (DBaaS), or Managed Databases, permits users to set up, operate, and scale databases without maintaining and managing their underlying technologies. It allows most organizations and individuals to opt for a cost-efficient solution. Database administrators (DBA) face more challenges and problems while increasing workloads and database complexity as most IT organizations move towards an application-centric approach.

Amazon Aurora is a relational database created especially for the cloud. It combines the accessibility and affordability of open-source databases with the functionality and performance of standard enterprise databases. It is wholly managed and works with PostgreSQL and MySQL.

When comparing AWS Aurora vs RDS, Aurora offers a cloud-native architecture with better scalability and availability, making it a preferred choice for high-performance applications. RDS is a managed database service for SQL (Structured Query Language) offered by Amazon, much like Aurora. It supports various database engines for managing and storing data and includes relational database maintenance tasks, including data migration, backup and recovery, and patching.

In the Amazon Aurora vs RDS debate, RDS supports more database engines but with traditional architecture, while Aurora postgresql vs RDS postgresql highlights Aurora’s superior performance and automatic scaling. Overall, Amazon RDS vs Amazon Aurora decisions depend on workload requirements, cost considerations, and desired scalability.

In the debate about Amazon Aurora VS RDS, RDS supports more database engines, but the ones with classical architecture. At the same time, Aurora PostgreSQL VS RDS PostgreSQL emphasizes the greater performance with automatic scaling on the part of Aurora. Generally, the factors of workload, cost, and scale of the Amazon RDS VS Amazon Aurora kind of decisions come into play.

In 2025, Amazon Aurora continues to demonstrate its dominance as the fastest-growing relational database service, experiencing a robust 150% year-over-year growth rate in 2024, as highlighted in the AWS re:Invent 2024 keynote. This exceptional growth is reflected in its market share, reaching 1.20%, making it a compelling choice for organizations seeking a robust and scalable database solution.

Widely adopted globally, Amazon Aurora boasts over 100,000 customers spanning 185 countries, cementing its position as a globally trusted platform (Source: Amazon Web Services website). Furthermore, the 2025 RightScale State of the Cloud Report affirms that Amazon Aurora is the go-to choice for production workloads, emphasizing its reliability and performance in critical business operations.

Simultaneously, Amazon RDS maintains its status as the most popular relational database service, with a substantial 5% market share, catering to an impressive 2 million customers across more than 190 countries (Source: Amazon Web Services website). Its versatility is evident in its application across various workloads, including web, mobile, and enterprise applications, showcasing its adaptability to diverse organizational needs.

Amazon Aurora delivers over 500,000 SELECTs/sec and 100,000 UPDATEs/sec, five times higher than MySQL running the same benchmark on the same hardware. (Source: Amazon Web Services)

The 2025 RightScale State of the Cloud Report reinforces Amazon RDS’s cost-effectiveness, positioning it as a pragmatic solution for running relational om’.databases in the cloud. In summary, these statistics underscore the widespread appeal, reliability, and cost-effectiveness of Amazon Aurora and RDS in meeting organizations’ diverse demands globally.

Before opting for the best solution for your organization, you should consider multiple factors like security, scalability, monitoring, performance, high availability, management, capacity planning, and operational cost. If any organization wants to run its services in Amazon Web Service (AWS), there are two best platforms: Amazon Aurora and RDS. Both services provide multiple options to assist in database administration.

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What Is Amazon Aurora and How Does It Work?

Amazon Aurora is a cutting-edge relational database service that was created and offered by AWS in 2014. Amazon designed Aurora to work with MySQL 5.6 and PostgreSQL, which were built for the cloud service. Aurora Postgres delivers five times better performance than MySQL and three times better than PostgreSQL, with the reliability, security, and availability of high-end commercial AWS database services at one-tenth the price.

In addition, Aurora PostgreSQL syncs with MySQL and PostgreSQL and offers various special features, such as security, durability, migration, and more. Moreover, it stunts maintenance costs without sacrificing performance.

AWS Aurora allocates the database storage volume in 10 GB logical blocks without your intervention, also known as the Protection group. The data available in the protection group is reproduced across six storage nodes, which are automatically allocated across three separate availability zones (AZs) in the Amazon Aurora cluster. If data fails in one AZ, it aims to recover it in another AZ.

When you create a cluster, it automatically consumes data. If data increases and exceeds storage capacity, the service engine seamlessly expands its volume to meet the requirement and auto-scales up to 64 TB.

This dynamic scaling capability showcases the performance and flexibility of AWS Aurora vs RDS, making it a powerful option for organizations considering Amazon Aurora vs RDS for their workloads.

However, the real highlight lies in the dynamic scaling capability that shows the performance and flexibility of AWS Aurora vs RDS, thus making it the best alternative for organizations thinking of Amazon Aurora vs RDS for their specific workloads.

Aurora Database Cluster

This database engine consists of multiple DB instances and a cluster volume that primarily aims to hold the data for the DB instances. Aurora Postgres is a virtual database storage volume that spans various Availability Zones into a single AWS region and houses a copy of the DB cluster data. This is all about how your DB cluster can permit a failure of the Availability Zone without interruption of services and any data loss. Here, we have two Aurora DB instances: Primary DB and Aurora Replica.

This design exemplifies how your Aurora DB cluster can permit a failure of the Availability Zone without interruption of services and any data loss (Aurora PostgreSQL vs RDS PostgreSQL). This is geared towards providing high availability, data durability, and automated failover, these being the major benefits considered when evaluating Amazon RDS vs Amazon Aurora or AWS Aurora vs RDS for enterprise-grade applications.

A) Primary DB Instance

This instance performs all data input modifications (read and write operations) to the cluster volume. Every cluster in this AWS database service consists of at least one primary DB instance.

B) Aurora Replica

Replica only supports read operations and joins the same data cluster as the primary DB instance connects. Each DB cluster can support up to 15 Aurora replicas, which can be distributed across the Availability Zones that a DB cluster spans across the AWS region.

Aurora Replica has two purposes. You can ask them to remove your application’s only read operations. It also helps to increase availability. If the writer DB instance fails and is unavailable in a single master cluster, the failover mechanism (Aurora) automatically approaches and replaces a new writer DB instance (Amazon Aurora vs RDS).

All DB instances can perform read/write operations in the Aurora database multi-master cluster. Aurora Replica doesn’t apply to a primary instance’s notions in this particular case and is used for multiple read-only operations (AWS Aurora vs RDS, Aurora PostgreSQL vs RDS PostgreSQL, Amazon RDS vs Amazon Aurora).

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What Features Make Amazon Aurora Suitable for Enterprise Use?

1) Availability and Durability

AWS Aurora offers a feature that is self-healing and fault-tolerant storage built for the cloud. It is designed to provide an excellent availability of 99.99%, and the cloud storage replicates six copies of your data that can be created across three Availability Zones. Furthermore, due to the safety purpose of storage failure, it continuously backs up the data to Amazon S3.

2) Higher Security

This web service provides numerous levels of strong security for protecting your database, such as encryption at rest using AWS Key Management Service (KMS), encryption of data in transit operating SSL, and network isolation using Amazon VPC. The same cluster also provides automatic backups, replicas, and snapshots (AWS Aurora vs RDS, Amazon Aurora vs RDS, Aurora PostgreSQL vs RDS PostgreSQL, Amazon RDS vs Amazon Aurora).

For this reason, many companies compare AWS Aurora vs RDS, Amazon Aurora vs RDS, Aurora PostgreSQL vs RDS PostgreSQL, and Amazon RDS vs Amazon Aurora while picking their security and scaling database solution.

3) Fully Managed

An Amazon Relational database service (RDS) manages the Amazon Aurora database. As a result, users don’t need to worry about database management services tasks like setup, configuration, backups, software patching, and hardware provisioning.

Organizations looking at managed database services such as AWS Aurora vs RDS and Amazon Aurora vs RDS are considering this experience as one of the reasons.

4) Migration Support

Amazon Aurora makes it simple to migrate your local database using MySQL dump and PostgreSQL dump commands.

This particular ease of transition is generally emphasized in Aurora PostgreSQL vs RDS PostgreSQL and Amazon RDS vs Amazon Aurora comparisons, especially when companies are bolstering their cloud migration strategies.

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What Are the Ideal Use Cases for Amazon Aurora?

1) Mission-Critical Applications

Amazon Aurora is engineered for mission-critical applications where high performance and availability are non-negotiable. Examples include financial systems, healthcare databases, and other applications where downtime or performance degradation is unacceptable. Its architecture, with replication across multiple Availability Zones, ensures fault tolerance and reliability.

2) Mixed Workload Scenarios

In scenarios demanding a blend of read and write operations, such as e-commerce platforms and gaming applications, Amazon Aurora versus RDS shines. Aurora’s storage engine’s distributed nature allows for efficient handling of read and write queries, making it suitable for applications with dynamic and demanding workloads.

3) Compatibility Advantage

Amazon Aurora’s compatibility with MySQL and PostgreSQL is a significant advantage over RDS. Organizations leveraging these popular database engines can seamlessly transition to Aurora with minimal friction. This makes it an attractive option for businesses looking to enhance performance without undergoing significant database architecture changes.

4) Real-Time Analytics

Amazon Aurora’s high-performance capabilities make it an excellent choice for real-time analytics applications. Businesses requiring instant insights into large datasets, such as those in the financial sector or online retail, can leverage Aurora’s robust architecture to efficiently handle complex queries and analytics workloads. The seamless integration with popular analytics tools enhances its suitability for organizations prioritizing data-driven decision-making.

5) Geographically Distributed Applications

Amazon Aurora’s multi-AZ deployment options are advantageous for applications with a global user base or those requiring data distribution across different regions. Its ability to replicate data across multiple Availability Zones ensures low-latency database access, enhancing the user experience. This makes Amazon Aurora a preferred choice for geographically distributed applications, such as content delivery platforms or global e-commerce solutions.

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What is Amazon RDS (Relational Database Service)?

Amazon RDS is a cloud-based relational database service that allows you to manage and scale your application in the cloud. RDS has many database engines, such as Microsoft SQL Server, Oracle Database, MariaDB, MySQL, PostgreSQL, and Amazon Aurora. It automatically backs up your database and updates the latest software.

The service engine offers various instant types with different resources, such as network capability, storage options, CPU, and memory. It is a fully managed RDBMS service.

With the AWS Command Line Interface and AWS Management Console, administrators can control RDS with the AWS Command Line Interface, which can decrease or increase your RDS requirements within minutes. These interfaces are used to deploy database instances to apply specific user settings. Additionally, RDS users can operate Access Management and AWS Identity to define and set permissions to access an RDS database.

What Features Make Amazon RDS Suitable for Enterprise Use?

• Amazon RDS automatically replaces the host if the hardware fails
• No upfront payment is needed as an export database from Amazon RDS charges only for the resources consumed by the user and it also offers a few Aurora serverless pricing models like ‘Reserved instances’, and ‘On-Demand’.
• It provides high security for accessing their database and related services.
• This relational database service engine manages automatic backup timings and backs up the transaction log for up to five minutes.
• Users can capture snapshots of their database instances stored in Amazon S3 daily.
• AWS RDS vs Aurora service engine automatically acquires all the patches for the database software.

Pros of RDS

• Simplified disaster recovery and automatic failover
• Maintenance of hardware
• Possesses an automatic backup
• Allocation of storage automatically

Cons of RDS

• There are only five read replicas.
• Lacks automatic handling of compression
• There is no assurance of CPU and storage performance.
• No automatic performance optimization
• It does not provide a guarantee against data loss
• Lacks root access to the server

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What Are the Ideal Use Cases for Amazon RDS?

1) Versatility Across Workloads

Amazon RDS is known for its versatility and ability to cater to various workloads. Whether running a small-scale application or managing large enterprise databases, RDS provides a scalable and reliable solution. This adaptability makes it suitable for businesses of varying sizes and industries.

2) Application-Centric Support

Amazon RDS is well-suited for diverse application scenarios, including web, mobile, and enterprise applications. Its compatibility with multiple database engines, including MySQL, PostgreSQL, SQL Server, and Oracle, ensures businesses can choose the engine that best fits their application requirements.

3) Flexibility in Technology Stacks

One of Amazon RDS’s critical strengths is its support for various database engines. This flexibility is crucial for businesses with diverse technology stacks. Whether your applications rely on MySQL, PostgreSQL, SQL Server, or Oracle, Amazon RDS provides a unified management interface, simplifying database administration across different technologies.

4) DevOps Environments and Testing

Amazon RDS is well-suited for DevOps environments, providing a scalable and automated database solution. Development and testing processes can benefit from RDS’s ease of deployment and management, allowing teams to concentrate on application development rather than database administration. With features like automated backups and version updates, RDS streamlines the development lifecycle, making it a go-to choice for organizations embracing DevOps practices.

5) Compliance-Driven Databases

In industries where regulatory compliance is paramount, such as healthcare or finance, Amazon RDS offers features that simplify adherence to strict compliance standards. RDS provides rest and transit encryption, ensuring data security and privacy. With built-in backup and recovery options, organizations can confidently manage databases following compliance requirements, making Amazon RDS an ideal choice for sectors with rigorous data governance standards.

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What Are The Factors to Consider Before Deciding Between RDS and Aurora?

We contrasted the two database services feature by feature. Before choosing the service for Amazon Aurora vs RDS, which is best for you, look at some other crucial factors.

1) Cost

Aurora is typically more expensive than RDS for the same workloads. AWS Aurora pricing depends on the instance’s kind, size, and EBS volume. Instance size is primarily the determining factor, and storage is charged based on actual usage. Remember that read replicas are more expensive on both platforms.

2) Availability

Data backup is crucial for production databases, in particular. In comparison, Aurora RDS offers greater availability and resilience because of its unique storage model and the ability to perform continuous backups. She restores with a very low recovery point aim.

3) Database Engine Support

Aurora versus RDS supports only MySQL and PostgreSQL. Therefore, you must use RDS to operate additional database engines, such as SQL Server.

How Does the Performance of Amazon Aurora Compare to Amazon RDS?

Success Study: Cloud Infrastructure Automation for a Financial Services Firm

 Choosing the right database service is just one part of a broader cloud strategy. In a notable case, Veritis supported a finance and insurance company with full-fledged infrastructure automation and cloud enablement. As part of this transformation, selecting and optimizing the right database services played a critical role in achieving scalability, performance, and compliance. Whether using Amazon Aurora or RDS, aligning the database choice with specific business needs was essential to the client’s cloud success.

This case illustrates how the right infrastructure and database decisions, when combined, drive reliable, scalable, and secure cloud environments.

To read the complete success story, explore the full case study: Full-Fledged Infrastructure Automation & Cloud Support to Finance and Insurance Company