Amazon RDS for Aurora vs Heroku Postgres: What are the differences?

Introduction

In this article, we will compare and highlight the key differences between Amazon RDS for Aurora and Heroku Postgres. Both Amazon RDS for Aurora and Heroku Postgres are popular relational database services used by developers and businesses to store, manage, and retrieve data. However, there are several significant differences between the two that we will explore in the following paragraphs.

1. Scalability: One major difference between Amazon RDS for Aurora and Heroku Postgres is the scalability options they offer. Amazon RDS for Aurora provides automatic scaling capabilities, allowing the database to handle increasing workloads efficiently. It can automatically add replicas to distribute the load and scale seamlessly as the data grows. On the other hand, Heroku Postgres does not have built-in automatic scaling and requires manual configuration to handle increased load.

2. High Availability: Amazon RDS for Aurora is designed to provide high availability and fault tolerance. It replicates data across multiple Availability Zones (AZs) within a single region, ensuring that data is still accessible even in the event of a localized outage. Heroku Postgres, while also providing some level of high availability, may not have the same level of redundancy and fault tolerance as Aurora.

3. Backup and Restore: Amazon RDS for Aurora offers automatic backups and point-in-time recovery (PITR) capabilities. It provides continuous backups with a retention period of up to 35 days, allowing users to restore the database to a specific point in time. Heroku Postgres also provides backup and restore options, but the retention period might be limited and it may not offer the same level of granularity as Aurora for PITR.

4. Management and Monitoring: Amazon RDS for Aurora provides a comprehensive management console and monitoring tools, allowing users to easily manage and monitor their databases. It offers detailed performance metrics, automated software patching, and other essential management features. Heroku Postgres also offers management tools, but the level of granularity and control may not be as extensive as Aurora.

5. Integration with Cloud Ecosystem: Amazon RDS for Aurora seamlessly integrates with other AWS services such as Amazon CloudWatch, AWS Identity and Access Management (IAM), AWS Database Migration Service (DMS), and more. This integration enables users to leverage the complete AWS ecosystem for their database needs. Heroku Postgres, while offering some integrations, may not have the same level of integration and compatibility with AWS services.

6. Cost Structure: The cost structure of Amazon RDS for Aurora and Heroku Postgres differs. Amazon RDS for Aurora offers an on-demand pricing model, where users pay for the actual resources used. Heroku Postgres, on the other hand, follows a different pricing model and may have additional costs depending on the features and add-ons used.

In summary, the key differences between Amazon RDS for Aurora and Heroku Postgres lie in scalability options, high availability capabilities, backup and restore functionalities, management and monitoring tools, integration with the cloud ecosystem, and cost structures. These differences make Aurora a preferred choice for users looking for a highly scalable and fault-tolerant database solution, while Heroku Postgres may appeal to users who prioritize simplicity and ease of use.