Databricks lets developers build AI apps in just 5 minutes. Here’s how.
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Databricks just made app development a piece of cake. Databricks Apps is a new capability announced by Ali Ghodsi’s company. It allows enterprise developers quickly create production-ready AI and data applications with just a few clicks. The service is available in public preview as of today. It provides users with an experience based on templates, where they connect relevant data to frameworks and create a fully-functional app that can run within the Databricks environment. According to the company it can be used in just five minutes to create and deploy secure apps. What can you expect from Databricks apps?
Like Snowflake, Databricks offers its customers the option to create apps using their own data. Users can build apps such as interactive dashboards that dig into specific insights, or AI-driven systems such as chatbots and fraud detection programs. The developers must handle many critical aspects, including provisioning infrastructure, managing data, ensuring compliance, and manually bolting in integrations to control access and define who can use the app. This often makes the whole development process complex and time-consuming.
“App authors had to become familiar with container hosting technologies, implement single sign-on authentication, configure service principals and OAuth, and configure networking. The apps they created relied on integrations that were brittle and difficult to manage,” Shanku Niyogi, the VP of product management at Databricks, tells VentureBeat.
To change this, the company is now bringing everything to one place with the new Databricks Apps experience.
With this offering, all a user has to do is select a Python framework from a set of options (Streamlit/Dash/Gradio/Flask), a template of the type of app they want to develop (chatbot or data visualization app) and configure a few basic settings, including those for mapping resources (like data warehouses or LLMs) and defining permissions. Once the basic setup has been completed, the app will be deployed into the Databricks environment of the user, which allows them to use the app themselves or to share it with other members of the team. The app will prompt users to use single sign-on authentication when they log in. Further, if needed, the developer will also get the option to customize the developed app and test their app code in their preferred IDE (integrated development environment).
On the backend, Niyogi explained, the service provisions serverless compute to run the app, ensuring not only faster deployment but also that the data does not leave the Databricks environment.
“Each app is fortified with robust security measures for seamless and secure user access. The integration with Unity Catalog offers comprehensive data management and governance capabilities. Apps inherit the network protections from your workspace. This ensures a multi-layered approach to security for sensitive data and apps. However, Niyogi noted that the company is working to expand to more tools, languages and frameworks, making secure app creation easier for everyone.
“We’ve started with Python, the #1 language for data. Databricks Apps allows anyone familiar with Python to create an app using code. Anyone with an existing application can easily import it into Databricks Apps. We support all Python IDEs. The number of enterprises that have tested Databricks Apps is expected to grow in the coming months. With the public preview launching today, the number is expected to grow in the coming months.
Notably, Snowflake, Databricks’ biggest competitor, also has a low-code way to help enterprises develop and deploy data and AI apps.
However, Databricks claims to distinguish itself with a more flexible and interoperable approach.
“Databricks Apps support Dash, Gradio Flask and Shiny, as well as Streamlit. It also supports more versions than Snowflake. The tools that developers use to create apps are also their choice. Stay informed! Subscribe to receive the latest news daily in your email.
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