With Databricks, developers can now create AI apps in 5 minutes: Here’s how

Databricks makes app development easy. The company, led by Ali Ghodsi, announced Databricks Apps, a feature that enables enterprise developers to quickly build production-ready data and AI applications in a few clicks.

This service, currently available in public preview, provides a template-based experience to users. Users can connect relevant data and frameworks of their choice into fully functional apps that can run within their own Databricks environment.

The company says it allows you to create and deploy secure apps in just five minutes.

This announcement comes even as companies are bullish on the potential of data-driven applications, which require operational support throughout the development cycle, from provisioning the right infrastructure to ensuring security and access controls for developed apps. This was done at a time when I was still struggling with the complications above. .

What do you expect from Databricks Apps?

Like Snowflake, Databricks has long offered customers the ability to build apps that leverage data hosted on its platform. Users can already build applications such as interactive dashboards to drill down to specific insights and build advanced AI-driven systems such as chatbots and fraud detection programs.

However, no matter your development choice, the process of getting reliable apps into production in a secure and controlled manner is not easy.

Developers need to be aware of any number of aspects of their development pipeline, from provisioning and managing infrastructure, ensuring data governance and compliance, to manually bolting integrations for access control, and defining who can and cannot use an app. You need to do more than just create an app to handle important aspects of the process. This often makes the entire development process complex and time-consuming.

“App creators had to become familiar with container hosting technology, implement single sign-on authentication, configure service principals and OAuth, and configure networking. The apps they created were vulnerable and unmanageable. It relied on difficult integrations,” Shank Niyogi, vice president of product management at Databricks, tells VentureBeat.

To change this, the company is now bringing everything together in one place with the new Databricks Apps experience.

With this service, all a user has to do is choose a Python framework from a set of options (Streamlit/Dash/Gradio/Flask) and choose a template for the type of app they want to develop (chatbot or data visualization app). All you have to do is select and configure. Some basic configuration, such as mapping resources (such as data warehouse or LLM) and defining permissions.

Once the basic setup is complete, the app is deployed to your Databricks environment and ready for you to use yourself or share with others in your team. When someone else logs in, the app automatically requests single sign-on authentication. Additionally, if desired, developers also have the option to customize the apps they develop and test their app code in their preferred IDE (Integrated Development Environment).

On the backend, Niyogi explained that the service provisions serverless compute to run apps, speeding up deployments as well as ensuring data never leaves the Databricks environment.

“Each app is hardened with robust security measures for seamless and secure user access. Additionally, integration with Unity Catalog provides comprehensive data governance and management capabilities, allowing apps to It inherits network protection and ensures a multi-layered security approach for sensitive data and applications,” he explained.

At this time, Databricks Apps only supports Python frameworks. However, Niyogi said the company is working on expanding to more tools, languages ​​and frameworks, making it easier for everyone to create secure apps.

“We started with Python, the number one language for data. Anyone familiar with the Python framework can create an app in code, and anyone with an existing app can use it. Easily onboard to Databricks apps. We support any Python IDE. We work with our ISV partners to enable their tools to support Databricks apps and add support for other languages ​​and frameworks. We are working to make it possible,” he added.

About 50 companies are already testing the beta version of the Databricks app, including Addi, E.ON Digital Technology, SAE International, Plotly, and Posit. With public preview starting today, we expect that number to grow in the coming months.

Notably, Databricks’ biggest competitor, Snowflake, also has a low-code way to help enterprises develop and deploy data and AI apps.

However, Databricks claims to differentiate itself with a more flexible and interoperable approach.

“Databricks Apps supports Streamlit plus Dash, Gradio, Flask, Shiny, and more versions of Streamlit than Snowflake. Developers can build apps using the tools of their choice. We will continue to develop this flexible approach and add support for more languages, frameworks, and tools,” Niyogi noted.