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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.

Advice on Amazon Aurora and Heroku Postgres

Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.

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Replies (2)
David Weinberg

Good balance between easy to manage, pricing, docs and features.

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Max Musing
Founder & CEO at BaseDash · | 1 upvotes · 49.1K views

DigitalOcean's offering is pretty solid. Easy to scale, great UI, automatic daily backups, decent pricing.

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Pros of Amazon Aurora
Pros of Heroku Postgres
  • 14
    MySQL compatibility
  • 12
    Better performance
  • 10
    Easy read scalability
  • 9
    Speed
  • 7
    Low latency read replica
  • 2
    High IOPS cost
  • 1
    Good cost performance
  • 29
    Easy to setup
  • 3
    Follower databases
  • 3
    Dataclips for sharing queries
  • 3
    Extremely reliable

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Cons of Amazon Aurora
Cons of Heroku Postgres
  • 2
    Vendor locking
  • 1
    Rigid schema
  • 2
    Super expensive

Sign up to add or upvote consMake informed product decisions

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What is Amazon Aurora?

Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.

What is Heroku Postgres?

Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

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What companies use Amazon Aurora?
What companies use Heroku Postgres?
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What are some alternatives to Amazon Aurora and Heroku Postgres?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
See all alternatives