Azure Databricks vs. Heroku Platform

Centralised notebooks are out directly into production. This can lead to poorly engineered code. It is very good for fast queries and our data team are always able to provide what we ask for. It is a big cost to our business so it is important it runs efficiently and returns on our investment.

Incentivized

Heroku is very well suited for startups looking to get a server stack up and running quickly. There is little to no overhead when managing your instances. However, you'll need a background in basic DevOps or system management to make sure everything is set up correctly. In addition, it's easy to accidentally go crazy on pricing. Make sure you're only creating the server instances you need to run the base application and set up an auto-scaler plugin to handle peaks.

Incentivized

• Data Processing and Transformations based on Spark
• Delta Lakehouse when clubbed with an external cloud storage
• Governance using Unity Catalog to unify IAM
• Delta Live Tables is a product, which although relatively newer, has a great potential with the visuals of a pipeline.

Incentivized

• Heroku has a very simple deployment model, making it easy to get your application up-and-running with minimal effort. We can focus on our efforts the unique aspects of our application.
• The robust add-on marketplace makes it easy to try out new approaches with minimal effort and investment -- and when we settle on a solution, we can easily scale it.
• Heroku's support is quite good -- their staff is quite technical and willing to get into the weeds to diagnose even complicated problems.

Incentivized

• Intuitive interface
• Ease of use
• Providing FAQ or QRGs

Incentivized

• Large price jumps between certain resource tiers (2x Dyno for $50 per month versus Performance Dyno for $250). Free Postgres next jumps to $50 per month.
• Marketing/Branding to non-technical stakeholders. As the years pass, I've had to fight more to convince stakeholders on the value of Heroku over AWS.
• Improve Buildpack documentation. This is one area where Heroku's documentation is fairly confusing.

Incentivized

Heroku is easy to use, services a ton of functions for you out of the box, and provides a means to get a software product off the ground and managed quickly and easily. The tools provide allows a small to medium size org to move very quickly. The CLI tools provided make managing an entire technical infrastructure simple.

Incentivized

The developers are able to switch between Python and SQL in the Notebook which allows the collaboration of SQL analyst and Data scientist. The integration of Mosaic AI allows users to write complex codes in natural languages. Unity catalog has centralized the security and governance features and simplified the process of maintaining it

Incentivized

Easy to use web based console and easy to use command line tools; deployment is done directly from a GIT repository. What more could you ask for? The one thing that keeps me from giving it a 10 is that custom build packs are almost incomprehensible. We used one for a while because we needed cairo graphics processing. Fortunately, I was able to figure out a different way to do what we needed so that we could get off the custom build pack.

Heroku availability correlates pretty strongly to AWS US EAST availability. We had a couple of times where there was a Heroku-specific issue but not for the last 7-8 months.

The only issue that I ever have is that about 1 out of 20 deployments (git push) will hang and need to be cancelled and done again.

I've used it for many years without facing any major problem. It's not hard at all to get used to it, it's documentation is outstanding and simple. We are close to 2020 and I don't think most of the existing companies or startups should still face old problems such as wasting time deploying code and calculate computing resources.

Incentivized

Be ready to pay a bit more than expected in the beginning if you're migrating from a big server. The application is probably not ready for the change and you have to keep improving it with time.

It's also important to consider that you can't save anything to the disc as it will be lost when your application restarts, so you have to think about using something like S3.

Incentivized

I have found Azure Databricks to be much better than Snowflake for handling bigger, diverse data types. Snowflake is much simpler and better for smaller warehousing. The real time processing is much better in Azure Databricks and we have much more language options. Snowflake is more expensive but simpler to use. Both are great for different needs.

Incentivized

Heroku is the more expensive option for hosting compared to some of the cloud platforms we investigated, but it's worth it for us because of the plug-and-play nature of Heroku deployment. We can be up and running in a few minutes and know with precision how much it will cost us each month to run the application, unlike Amazon Web Services where you have to go to great pains to configure it correctly or else you might end up with a shocking monthly bill. Overall, spending the time to configure Amazon Web Services or one of its competitors is likely the more affordable and powerful choice, because you have control over so many specifics of the configuration. But it also requires the burden of continuing to maintain and update your AWS instance, whereas with Heroku they take care of security fixes and platform upgrades. It's a great service and we are happy to pay the extra cost for the value-adds Heroku provides.

Incentivized

• The support team is amazing, they help you at every stage of the projects, from sales to delivery.
• On a framework level, it has had an amazing impact and has reduced the clients overall data platform costs by a staggering 65%
• There has been a 40% Manual work requirement on average for the clients when they move to Azure Databricks Data Platform

Incentivized

• It has been critical in seamlessly operating our platform with runs all of our programs.
• It has been impressive with its ability to scale quickly which results in the growth of our work.
• It allows for tracking of different features which allows for quick problem solving which saves us time.