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Guide to Cost Factors for Amazon’s RDS Pricing

Amazon sports a complex pricing model. As simple as the pay-for-what-you-use model sounds, there are several nuances to every service from data used to computing components chosen that can easily let users blow through their entire budget. That’s not to say AWS is an inherently expensive platform and can be adapted to with proper planning and understanding of the contributing factors to billing.

What is the Relational Database Service?

Amazon Relational Database Service (RDS) provides database engines of multiple types and instances. Users can manage and scale these databases to suit their needs and configure them with the most needed parts. Though Amazon does claim that its performance and scalability can match its competitors while remaining a mere fraction of the cost, this is the ideal circumstance with proper price control enacted.

Regular monitoring and optimization are indispensable. Without this, RDS costs can spiral as performance issues or unused capacities go unnoticed. Continuously analyze your workload’s performance and adjust resources as needed to maintain an optimal balance between cost and performance. To optimize costs effectively and avoid unnecessary expenses in managing RDS, it is crucial to steer clear of several common pitfalls. First, ensure you do not overprovision resources; accurately assess your workload requirements and select the appropriate instance types and storage options. Overprovisioning can significantly inflate your RDS costs without adding value.

Just for reference, RDS is one of the services that can take advantage of AWS’ Free Tier category. For the first year after signing up with AWS, users receive 750 hours of database usage per month for MySQL, PostgreSQL, MariaDB, or SQL Servers using single-AZ db.t2.micro, db.t3.micro, and db.t4g.micro Instances. Additionally, users can access 20GB of SSD cloud storage and 20GB of storage dedicated to snapshots and backups. Regardless of how much they used this service during the trial period or if they even used it, this offering will expire after the first twelve months of the account’s lifespan, so use this offer to learn and adapt to the RDS pricing model.

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Database Engine Pricing

The choice of RDS instance significantly affects the overall cost. AWS provides a variety of instances that are tailored for different types of workloads—ranging from compute-intensive to memory-heavy, or storage-optimized tasks. Each category has its pricing structure based on performance capabilities and resource allocations. It’s crucial to select an instance that best fits your specific application demands to ensure you are not overspending on superfluous resources.

  • On-Demand Instances: Users have the flexibility to pay by the hour without any upfront fees or long-term commitments. If a database is utilized for less than an hour, billing is done in one-second increments with a minimum charge of 10 minutes. The billing starts the moment the instance is started and stops as soon as it is stopped. This option is the default for all engines.
  • Reserved Instances: Amazon RDS Reserved Instances offer users the opportunity to secure significant discounts by committing to 1 or 3-year terms. The pricing structure accommodates users’ resource needs, ensuring flexibility and cost savings. When considering payment options, users can choose from three distinct plans to maximize their savings potential:
    • Opting for no upfront fees guarantees a 29% discount compared to the On-Demand rate.
    • Selecting a partial upfront payment, ranging from 0% to 99%, unlocks savings of up to 33% for 1-year plans and 52% for 3-year plans.
    • For those looking to make a full upfront payment, substantial savings of up to 34% on 1-year plans and 53% on 3-year plans are available. These options empower users to tailor their payment strategy to achieve the most advantageous cost benefits for their Amazon RDS Reserved Instances.

Amazon Aurora

AWS’s primary database engine, Aurora, is designed to be compatible with MySQL and PostgreSQL and offers great availability and scalability. It comes with dev kits for integrated machine-learning and serverless functionality. This engine primarily charges based on GB/month and I/O usage per million requests. Other features, including the Global Database, snapshots, and data transfers, also incur additional charges.


MariaDB, MySQL, and PostgreSQL

These three database engines work under the same pricing model as Amazon Aurora.  By comparison, PostgreSQL On-Demand instances are up to 10% more expensive than Aurora, depending on the size.  Otherwise, each engine shares the same storage, I/O, and data transfer rates.


Oracle and Microsoft SQL Server

Licensing makes these choices nearly double what the open-source options offer. It is possible to circumvent Oracle’s hefty price tags by just bringing your own Oracle license, bringing the hourly rates more in line with the open-source rates.
Amazon Aurora Database Pricing

Database Instance Pricing

Combined with the engine of choice, users will need to select an instance type, a vCPU for compute power, GiB RAM for memory, and networking options. Instance options range from db.t3.micro (has 2 vCPUS, 1 GiB RAM, and supports 2085 Mbps) to db.m5.24xlarge ( with 96 vCPUS, 384 GiB RAM, and does 19,000 Mbps). This process will involve extensive planning and considering what users need from the database.

Database Instance Pricing

Regional Pricing

Amazon distributes its services globally through Availability Zones (AZ). Each zone does have differing rates and outage protection options. Users will need to choose a region as well as consider the instance type, as the aforementioned rates are all dependent on the AZ of choice. Users do have the choice to deploy across multiple AZs simultaneously. These networks will consist of a primary DB with secondary DBs located at other AZs. This has the benefit of both providing low latency at fringe locations and data redundancy in the case of outages, failures, and traffic congestion.

Amazon RDS pricing varies based on the choice of database engine. Currently, RDS supports seven relational database engines with an eighth option for on-premises installation. Pricing does vary further on the instance type. On-Demand Instances allow users to pay by the hour, while Reserved Instances offer significant discounts for commitments of up to 1 or 3 years. The pricing model for each engine is different, with options for additional savings based on the user’s initial payment.

Amazon Aurora, the primary database engine, charges based on GB/month and I/O usage per million requests. MariaDB, MySQL, and PostgreSQL operate under the same pricing model as Amazon Aurora, with PostgreSQL On-Demand instances being up to 10% more expensive than Aurora depending on size. Oracle and Microsoft SQL Server choices are nearly double the cost of open-source options due to licensing, but users can bring their own Oracle license to align hourly rates with open-source options.

Storage Pricing

AWS offers diverse storage solutions such as General Purpose (SSD), Provisioned IOPS (SSD), and Magnetic storages. Each comes with its cost-to-performance ratio. General Purpose SSDs strike a good balance between cost and performance, making them suitable for a broad range of applications, whereas Provisioned IOPS SSDs are designed for I/O-intensive applications, albeit at a higher cost. Magnetic storage, while being the most economical, offers the least performance and might only suit less critical applications. I/O costs, which are charges per each input/output operation executed, should also be considered. Backup storage costs come into play when assessing how much data you are storing as backups, while backtrack storage applies if you need to enable the backtrack feature for any instance.



General Purpose SSD

This option is the standard and provides between 20 GiB and 64 TiB of general-purpose storage. I/Os do not count towards billing. General-purpose SSDs cost $0.115/GB per month.


Provisioned IOPS SSD

I/O capacity can be further adjusted for database requirements.  Users can scale from 1,000 IOPS to 80,000 IOPS and from 100 GiB to 64 TiB.  Provisioned IOPS SSDs cost $0.125/GB per month and $0.10/IOPS-month.


Magnetic Storage

Magnetic storage options range from 20 GiB to 3 TiB for the primary dataset and support backward compatibility. They cost $0.10/GB per month and $0.10/million requests for I/O.


SSD Storage Pricing

Other Price Factors

  • RDS Backup: Backups start at $0.095/GB per month, even after instance termination.
  • Snapshot export: Exports cost $0.01/GB of snapshot size. This will export snapshots in the Parquet format to an Amazon S3 bucket. This format doubles export speeds and requires a sixth of the space.
  • RDS data transfer: These rates will only apply to outbound transfers. Pricing is separated into tiers. It charges $0.09/GB for the first 10 TB/month and outbound transfers are free for the first 100 GB/month across all AWS regions and AZs outside of GovCloud and China.

The amount of data transfer involved can significantly influence the costs. AWS charges for data transfers both within and outside of its networks. Managing how data flows in and out of your RDS instances can lead to substantial cost savings. Tools such as Amazon CloudFront or AWS Direct Connect can be strategized to reduce these costs effectively.

Practices to Avoid

When managing RDS costs effectively, it’s crucial to avoid a few common pitfalls that can lead to overspending. Here are some key mistakes to avoid:

Over-Provisioning Resources: It’s easy to overestimate the capacity you need. Use AWS’s database scaling capabilities to adjust resources based on actual usage rather than predicted needs. Start with a smaller instance and scale up as needed.

Neglecting Reserved Instances: Reserved instances can save significant amounts over on-demand pricing. If you have steady-state database workloads, consider purchasing a reserved instance for lower costs.

Ignoring Automated Backups and Snapshots Costs: Although backups are essential for recovery plans, unchecked automated backups and snapshots can stack up and quietly increase costs. Regularly review and delete old backups that are no longer necessary.

Not Utilizing Cost Management Tools: AWS provides tools that can help track and optimize costs. Tools like AWS Cost Explorer help you understand your spending patterns and identify where you might be wasting resources.

Overlooking Different Storage Options: Not all data requires the highest-performing storage. Evaluate your storage needs and consider shifting less frequently accessed data to more cost-effective storage options.

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Dolan Cleary

Dolan Cleary

I am a recent graduate from the University of Wisconsin - Stout and am now working with AllCode as a web technician. Currently working within the marketing department.

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