Datacol vs Heroku

Heroku is a cloud Platform-as-a-Service (PaaS) supporting several programming languages that is used as a web application deployment model. Heroku is a great way to quickly build, innovate, and deploy a new product or service. It can be an excellent choice in early stage since not having to worry about operational issues reduce the time to market significantly.

Datacol provides similar features and developer experience but doesn’t limit flexibility and scalability provided by cloud. There comes a point, however, where many organizations outgrow their one-size-fits-all PaaS. Some common reasons include:

• Cost Efficiency

  Heroku’s platform runs on AWS, so you pay a margin on their costs for all the automation they have built for you. At the beginning, paying a 30% more for a $100 cloud bill isn’t so significant. However, when you start to spend more with Heroku and reach the point where you pay $1k-3k a month, a reduction of 30% becomes much more significant.

  Datacol is built over Google Cloud and have wider variety of instance types and pricing schemes to choose from, which allows you to better utilize the compute resources you’re paying for. Additionally you can lower cloud bill using sustained discount, if you’re fine with committing to Google for a longer term, you can reduce even more by buying reserved instances.

• Control & Security

  With Heroku, you lose fine-grained control and visibility over your servers. Installing custom software in your server stack is far from straightforward.

  Also, you don’t have options around how to structure your environment networking and security. Your application run in a multi-tenant environment. While with Datacol, you’ll have a much lower level control over your environment and the underlying cloud resources.

• Platform Limitations

  Heroku does not provide any regional redundancy and runs on AWS in the US East region or Europe West region. You can run apps in multiple regions and reduce risk of outage with Datacol.

Though Datacol provides a Heroku type control-layer over Google cloud, it does not limit your developer experience. You can anytime delete Datacol infrastructure from your account and applications will still be running and portable, giving you similar flexibility and control of a cloud.

Feature	Datacol	Heroku
Price & Performance	Cheaper & much better performance-per-dollar	2x-3x
Privacy	Private & Single Tenant	Limited & Multi-tenant
Regional Constraints	Supported Regions	Limited Regions
Security Compliance	Yes	No
Scheduler	Kubernetes based on containers	Heroku Dyno