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  1. Stackups
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  4. SQL Database As A Service
  5. Amazon RDS for Aurora vs Heroku Postgres

Amazon RDS for Aurora vs Heroku Postgres

OverviewDecisionsComparisonAlternatives

Overview

Amazon Aurora
Amazon Aurora
Stacks807
Followers745
Votes55
Heroku Postgres
Heroku Postgres
Stacks607
Followers314
Votes38

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.

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Advice on Amazon Aurora, Heroku Postgres

Jorge
Jorge

Jan 15, 2020

Needs advice

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.

51.8k views51.8k
Comments

Detailed Comparison

Amazon Aurora
Amazon Aurora
Heroku Postgres
Heroku Postgres

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.

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

High Throughput with Low Jitter;Push-button Compute Scaling;Storage Auto-scaling;Amazon Aurora Replicas;Instance Monitoring and Repair;Fault-tolerant and Self-healing Storage;Automatic, Continuous, Incremental Backups and Point-in-time Restore;Database Snapshots;Resource-level Permissions;Easy Migration;Monitoring and Metrics
High Availability;Rollback;Dataclips;Automated Health Checks
Statistics
Stacks
807
Stacks
607
Followers
745
Followers
314
Votes
55
Votes
38
Pros & Cons
Pros
  • 14
    MySQL compatibility
  • 12
    Better performance
  • 10
    Easy read scalability
  • 9
    Speed
  • 7
    Low latency read replica
Cons
  • 2
    Vendor locking
  • 1
    Rigid schema
Pros
  • 29
    Easy to setup
  • 3
    Follower databases
  • 3
    Extremely reliable
  • 3
    Dataclips for sharing queries
Cons
  • 2
    Super expensive
Integrations
PostgreSQL
PostgreSQL
MySQL
MySQL
PostgreSQL
PostgreSQL
Heroku
Heroku

What are some alternatives to Amazon Aurora, Heroku Postgres?

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

Google Cloud SQL

Google Cloud SQL

Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.

Amazon RDS for PostgreSQL

Amazon RDS for PostgreSQL

Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades, storage management, replication for high availability and back-ups for disaster recovery. With just a few clicks in the AWS Management Console, you can deploy a PostgreSQL database with automatically configured database parameters for optimal performance. Amazon RDS for PostgreSQL database instances can be provisioned with either standard storage or Provisioned IOPS storage. Once provisioned, you can scale from 10GB to 3TB of storage and from 1,000 IOPS to 30,000 IOPS.

ClearDB

ClearDB

ClearDB uses a combination of advanced replication techniques, advanced cluster technology, and layered web services to provide you with a MySQL database that is "smarter" than usual.

ElephantSQL

ElephantSQL

ElephantSQL hosts PostgreSQL on Amazon EC2 in multiple regions and availability zones. The servers are continuously transferring the Write-Ahead-Log (the transaction log) to S3 for maximum reliability.

Azure SQL Database

Azure SQL Database

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

Database Labs

Database Labs

We manage an optimized Postgres image. You focus on your core app, not on becoming a database administrator.

Cloud DB for Mysql

Cloud DB for Mysql

It is a fully managed cloud cache service that enables you to easily configure a MySQL database with a few settings and clicks and operate it reliably with NAVER's optimization settings, and that automatically recovers from failures.

Google Cloud SQL for PostgreSQL

Google Cloud SQL for PostgreSQL

With Cloud SQL for PostgreSQL, you can spend less time on your database operations and more time on your applications.

PlanetScaleDB

PlanetScaleDB

It is a fully managed cloud native database-as-a-service built on Vitess and Kubernetes. A MySQL compatible highly scalable database. Effortlessly deploy, manage, and monitor your databases in multiple regions and across cloud providers.

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