Heroku Vs. AWS: Which Cloud Solution Fits Your Development Needs?

It’s often said that Heroku is ideal for developers who prioritize rapid and straightforward application deployment. Meanwhile, AWS is seen as the ideal choice for applications requiring advanced scalability and intensive performance.

Yet, as both platforms have evolved, their offerings have expanded, and some overlaps have emerged, making it more challenging to distinguish their strengths and limitations.

For instance, AWS now includes user-friendly tools like Elastic Beanstalk for simplified deployments, while Heroku integrates with AWS services, leveraging its global infrastructure for greater scalability.

In this post, we’ll dive into how Heroku and AWS compare in terms of features, pricing, scalability, and more (without turning this blog into a technical manual).

Whether you’re a startup, a solo developer, or an enterprise, this comparison will help you decide which platform aligns best with your dev needs.

What Does Heroku Do?

Heroku is a Platform as a Service (PaaS) built on Amazon Web Services (AWS) infrastructure and, like DigitalOcean, is “developer-centric.” 

Here’s a preview of key Heroku features:

Image: Heroku features

This approach creates a more user-friendly experience for developers by abstracting much of the underlying infrastructure. And this doesn’t just free up your developers to focus on coding rather than managing the infrastructure. Heroku also provides a straightforward deployment process. 

There is more.

Here’s how AWS compares.

What Does AWS Do?

AWS is a more comprehensive cloud provider with over 240 services, including Infrastructure as a Service (IaaS), PaaS, and Software as a Service (SaaS) offerings. 

Consider this:

Image: Amazon Web Services cloud services and products

AWS is best known as an IaaS, providing extensive control over infrastructure but requiring more technical expertise to manage. It usually takes quite a bit of server configuration and management to get it right for your specific application demands.

However, this control makes AWS a powerful platform for advanced applications and experienced developers since any application can run at any size and performance level.

Heroku Or AWS: A Quick Comparison

Let’s get the tempo going with a quick overview of Heroku vs AWS.

	Heroku	Amazon Web Services (AWS)
Service type	Platform as a Service (PaaS)	Infrastructure as a Service (IaaS), PaaS, Software as a Service (SaaS)
Customizability and control	Managed environment; abstracts AWS infrastructure, minimizing management but limiting control	Full control over cloud resource allocation; granular control over server configuration for customized performance
Target audience	Developers, small and medium-sized teams and organizations	Experienced developers; all company sizes, although most suitable for enterprises
Ease of use	Easy to set up, run, and maintain	Requires more advanced technical knowledge
Security and Compliance	The abstraction limits security control	Detailed security control, such as IAM roles and RBAC  policies
Scalability	Supports horizontal scaling of containers (dynos)	Supports robust, automatic scaling — with a bit more configuration
Deployment process	Pull code directly from Git repositories	More complex; requires extensive configuration
Maintenance requirement	Minimal maintenance required	Requires active and skilled monitoring and maintenance
Integration capabilities	Developer-centric marketplace that offers 150+ add-ons, over 380 open-source buildpacks, and more	Seamless, native integration across more than 200 cloud services
Pricing	Tiered pricing based on add-ons and scalable containers deployed (Heroku Dynos)	Pay-as-you-go pricing by default; Diverse discount programs, including Savings Plans, Reserved Instances (RIs), and Spot Instances
Example use cases	Microservices, modular application design, dynamic web applications, rapid prototyping for startups and small teams/companies	High-performance computing, enterprise-level applications, custom infrastructure needs, applications requiring integration with a wide range of AWS services

With that overview in mind, let’s dive deeper into the key differences you’ll want to consider when deciding between AWS and Heroku.

Heroku Vs. AWS: Differences, Pros, Cons, And Cloud Costs To Decide On

Consider these:

1. Compute

With AWS, you can configure servers to meet specific performance needs, including CPU, memory, and storage options. It also supports auto-scaling, which dynamically adjusts the instance capacity based on demand to maximize resource utilization.

Heroku takes a different approach by abstracting infrastructure management. This managed approach simplifies the development process, freeing your team to concentrate on writing code instead of tinkering with server and cloud infrastructure optimization. 

However, this convenience comes at the cost of reduced control and customization over the underlying infrastructure. This sort of makes Heroku, as a service, more similar to Amazon Fargate than Amazon EC2.

Additionally, AWS provides a wide range of compute services, including Amazon EC2 (resizable virtual servers), AWS Lambda (event-driven serverless computing), Amazon ECS and EKS (container orchestration services for Docker and Kubernetes containers), AWS Fargate (serverless containers), and AWS Batch (batch processing at scale).

With Heroku, applications run in lightweight containers called dynos. Dynos adjust compute capacity up or down based on traffic and performance requirements. For example, additional dynos can be spun up when traffic spikes to maintain performance and prevent downtime. And, when traffic drops, the system scales down to minimize resource usage and costs.

This flexible scaling model is especially valuable for applications with unpredictable or seasonal traffic patterns. It also prevents over-provisioning while maintaining optimal resource allocation and performance.

Dynos also come in various sizes and types:

Consider this:

You can also pick from a selection of Dyno types (Eco, Basic, Standard, and Performance) based on your workload demands.

2. Ecosystem

Here’s the thing. Heroku operates primarily as an application deployment and management platform. Its focus on simplicity and ease of use ensures seamless integration with popular tools such as GitHub and Slack.

Its marketplace, Heroku Elements, also offers developer-centric, third-party add-ons for databases, monitoring, caching, and other functionalities. This supports rapid development and deployment and improves app capabilities without complex configuration.

Across the ring, AWS provides an extensive range of services, covering compute, storage, databases, machine learning, the Internet of Things (IoT), and more. This range of options empowers businesses to create highly customized solutions specific to their needs.

Another major AWS draw is its flexibility. Whether you’re scaling an application to meet increasing demand, experimenting with new technologies, or launching a completely different product line, AWS offers a comprehensive suite of services to support your journey.

You can grow, evolve, or even pivot to entirely new business models without the hassle of leaving the AWS ecosystem.

This extensive ecosystem simplifies transitions and reduces the need for external tools. However, its setup process can be complex and requires technical expertise. 

The user experience is also less intuitive than Heroku’s, which can be a barrier for newer teams.

Then again, AWS boasts a significantly larger developer community than Heroku. And this means it is much simpler to find technical support, resources, and a wide variety of add-ons to meet your needs.

3. Target audience

However, Heroku’s developer-first approach includes features like pre-configured environments, easy scaling options, and a rich marketplace of add-ons, all designed to accelerate development cycles. 

That means, while it may not offer the same level of flexibility and customization as AWS, Heroku delivers an intuitive platform that aligns with the priorities of agile development and microservices architecture.

That said, AWS is an excellent choice for larger teams and organizations looking to run high-performance applications. This is particularly true if your DevOps team needs and can manage complex infrastructure. For CI/CD workflows, your team can use AWS CodePipeline and CloudFormation for infrastructure as code (IaC).

Also, organizations requiring fine-grained control can use Amazon EC2 for custom server configurations and Elastic Load Balancing for traffic management.

That’s not all. Amazon Web Services offers advanced networking, storage/data lakes, and compute options, making it ideal for big data analytics and AI/ML training workloads.

Moreover, AWS has a more extensive global infrastructure. This ensures low latency performance and wider disaster recovery options.

4. Security and compliance options

Another significant advantage AWS has over Heroku is that it provides granular control over security settings, including firewalls, encryption, and access management (IAM and RBAC). The platform also complies with numerous standards, such as HIPAA, SOC 2, FedRAMP, and FIPS 140-2.

This means you can build applications that meet regulatory requirements without additional configuration.

The built-in compliance is particularly advantageous for organizations in regulated industries, allowing them to use even basic AWS services to achieve compliance.

Meanwhile, Heroku includes essential security features (built on AWS’s own) and adheres to standards like ISO and SOC 2. However, its compliance capabilities are limited compared to AWS.

For example, you’ll need Heroku’s enterprise offerings (such as Heroku Shield) for applications requiring HIPAA compliance, a more expensive option.

Additionally, Heroku abstracts much of the underlying cloud infrastructure, which can limit the level of customization available for security configurations.

5. Pricing models

Heroku’s tiered pricing is primarily determined by the number and type of dynos your application uses. In terms of compute pricing, a standard dyno with 512MB of RAM costs about $25 per month. A performance dyno with 14GB of RAM can cost up to $500 per month.

Picture this:

Image: Pricing for Heroku dynos

The pricing for Heroku’s full services varies based on service, data transfer needs, etc. Check the official pricing page for the most current prices. 

Heroku also offers a free tier for non-commercial applications. The offer provides between 550 and 1,000 dyno hours monthly. However, costs can increase considerably as your application scales and demands more resources.

AWS uses a more complex pricing structure based on variables such as service, region, instance type, and the disaster recovery options you choose. 

AWS’s pay-as-you-go approach ensures you only pay for the resources you use — unlike traditional fixed pricing models.

Here’s a quick overview of AWS pricing (with links to our in-depth guides for more details):

AWS also offers discounts for high usage, academic institutions, and non-profits, helping users optimize costs for diverse scenarios.

AWS Or Heroku: Which Cloud Hosting Provider To Choose Today

As we’ve discussed, Heroku and AWS have advantages in different areas. 

Heroku shines for smaller teams that may not require the extensive capabilities of AWS. It offers a developer-centric platform, making it particularly well-suited to teams and companies aiming to develop, deploy, and release products quickly and efficiently.

Alternatively, AWS is best suited to enterprises with experienced development teams that can navigate its Infrastructure as a Service (IaaS) approach. Its extensive configuration, scaling, customization options, and robust infrastructure make AWS the ideal platform for handling complex and high-demand applications.

That said, runaway costs have been a nightmare for many cloud customers over the last decade. If you’re concerned about your AWS spend, you’re not alone — and we can help.

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