Heroku vs Lambda Labs Comparison
Detailed comparison of features, pricing, and capabilities
Last updated May 1, 2026
Overview
Compare key metrics and features at a glance
Heroku
https://www.heroku.com
Heroku is a cloud platform as a service (PaaS) that enables companies to build, deliver, monitor and scale applications. The platform supports several programming languages and allows developers to deploy, manage, and scale modern apps without having to manage the underlying infrastructure. Heroku was acquired by Salesforce in 2010 and has since become one of the most popular PaaS solutions for web application deployment.
Lambda Labs
https://lambdalabs.com
Lambda Labs (also known as Lambda) is a cloud computing and hardware company specializing in GPU-based infrastructure for AI and machine learning workloads. The company offers on-demand and reserved GPU cloud instances, as well as on-premise GPU servers and workstations, designed for training and deploying deep learning models. Lambda serves researchers, startups, and enterprises seeking high-performance compute at competitive pricing compared to hyperscale cloud providers.
Quick Comparison
| Detail | Heroku | Lambda Labs |
|---|---|---|
| Category | Platform as a Service (PaaS) | AI Cloud Infrastructure |
| Starting Price | Contact Sales | $496.8/mo |
| Plans Available | 0 | 9 |
| Features Tracked | 17 | 15 |
| Founded | 2007 | 2012 |
| Headquarters | San Francisco, USA | San Francisco, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| api | ||
| API Monitoring | ||
| CLI Access | ||
| core | ||
| 1-Click Clusters | ||
| Application Metrics | ||
| Autoscaling | ||
| Bare Metal Instances | ||
| Block Storage | ||
| Dynos | ||
| GPU Instances | ||
| Heroku Dashboard | ||
| Heroku Key-Value Store | ||
| Heroku Pipelines | ||
| Heroku Postgres | ||
| Lambda Stack | ||
| Managed Inference and Agents | ||
| Multi-language Support | ||
| NVIDIA InfiniBand | ||
| No Egress Fees | ||
| Pay by the Minute | ||
| Private Cloud | ||
| Superclusters | ||
| Zero Throttling | ||
| custom | ||
| Buildpacks | ||
| integration | ||
| Add-ons Marketplace | ||
| Apache Kafka on Heroku | ||
| Heroku AppLink | Add-on | |
| Model Context Protocol (MCP) | ||
| security | ||
| Biometric Access | ||
| Security Patches | ||
| Single-Tenant Clusters | ||
| support | ||
| Dashboard Monitoring | ||
| Team Collaboration | ||
Pricing
Compare pricing plans and value for money
Heroku
Contact Sales
No pricing data available yet
Best For
Developers and startups needing quick Git-based deploys and managed scaling for modern web apps without infrastructure management.
Lambda Labs
From $496.8/mo
Price Components
- GPU Hour: $9.86/hour
- Reserved Capacity: $0/cluster
- GPU Hour: $6.16/hour
- GPU Hour: $6.69/hour
- GPU Hour: $3.99/hour
Best For
ML researchers and startups running large-scale distributed training jobs who prioritize cost efficiency and hardware control over managed service breadth.
Integrations
See which third-party services are supported
Supported Integrations
Coming Soon
Integration comparison data for Heroku, Lambda Labs is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
Heroku
Developers and startups needing quick Git-based deploys and managed scaling for modern web apps without infrastructure management.
- Git push deployment and dyno autoscaling enable instant scaling for web apps, unlike more complex setups on AWS or Azure.
- Managed data services like Heroku Postgres and Redis handle backups and HA, freeing developers from infra tasks.
- Native buildpacks for Node.js, Python, Java, and others simplify multi-language deploys versus custom configs elsewhere.
- Doubled 1GB slug limit supports AI/ML frameworks, boosting complex app compatibility.
- Transitioning to sustaining engineering mode limits new features, lagging behind innovative PaaS like Upsun.
- Runs atop AWS EC2 with dyno-based pricing that can escalate costs for high-traffic apps versus granular cloud options.
- Enterprise feature freeze pushes users toward Salesforce alternatives like Agentforce.
Lambda Labs
ML researchers and startups running large-scale distributed training jobs who prioritize cost efficiency and hardware control over managed service breadth.
- Per-second billing with no egress fees undercuts hyperscale providers on total cost of ownership for GPU workloads
- Bare metal access and Quantum-2 InfiniBand networking enable efficient distributed training across hundreds of GPUs
- Lambda Stack pre-installation eliminates environment setup friction, reducing time-to-training from days to minutes
- Smaller scale and regional availability compared to AWS, Google Cloud, and Azure limits enterprise multi-region deployments
- Limited managed services ecosystem; users handle more infrastructure complexity than with hyperscale competitors
Company Info
Company details and background
Heroku
Lambda Labs
Comparison FAQ
Common questions about comparing Heroku and Lambda Labs
No FAQs available yet