SAN FRANCISCO, June 20, 2023 — Databricks today introduced Lakehouse Apps, a new way for developers to build native and secure applications for Databricks. Lakehouse Apps will enable over 10,000 of his Databricks customers to unlock the value of their data within Lakehouse. Customers will now have easy access to a wide range of powerful applications running entirely within Lakehouse instances using their data with the full security and governance capabilities of Databricks.
The company also introduced new data sharing providers and AI model sharing capabilities to Databricks Marketplace, the only marketplace for data, AI, and applications, and announced the general availability of Databricks Marketplace at the Data+AI Summit.
“Lakehouse Apps will enable software providers to offer rich and secure apps within Lakehouse. It significantly reduces the friction in the His CTO of Databricks. “Furthermore, by expanding the Databricks Marketplace to cover AI models as well as apps, collaboration between companies evolves beyond the mere exchange of datasets to secure joint data-based computation and AI modeling. It meets a critical need in today’s business world.”
Lakehouse Apps Simplify Access to Data and AI
Data and AI applications are one of the fastest growing software categories, and the growth of generative AI and large language models (LLM) is fueling that trend. For the customer, Lakehouse Apps will be the most secure way to unlock the full value of data in Lakehouse, leverage Databricks native services, and run applications that extend his Databricks with new capabilities. Lakehouse Apps gives users secure and easy access to a wide range of innovative new applications, reducing the time and effort it takes to deploy, integrate, and manage data and AI applications.
The Lakehouse app offers developers uncompromising security
To bring the next generation of innovative applications into the hands of users, software vendors are looking for ways to securely access customer data, integrate with customer security and governance solutions, and efficiently run near customer data. Big hurdles need to be cleared. To ensure enterprise adoption, many developers take one of his two approaches. One is to limit the functionality of the application and rebuild critical parts of the application in SQL or the data platform vendor’s proprietary code. Or a build version of a product that customers must install and operate themselves is brittle and difficult to scale.
Lakehouse Apps helps developers overcome this dilemma with a native, secure, and no-compromise solution. Running directly on the customer’s Databricks instance, these apps easily and securely integrate with customer data, use and extend Databricks services, and enable users to interact with a single sign-on experience. . Data never leaves the customer’s instance. The Lakehouse app inherits the same security, privacy, and compliance controls as Databricks. Developers are not limited to proprietary frameworks and can use any technology and language to build apps.
Developers will also benefit from the ease of distribution by listing their Lakehouse apps on the Databricks marketplace, enabling customers to quickly discover and deploy their software.
Early development partners for Lakehouse Apps include Retool, Posit, Kumo.ai, and Lamini.
- Retool Customers will be able to leverage their data to quickly build and deploy internal apps. Developers can assemble her UI using drag-and-drop building blocks such as tables and forms, and create queries to manipulate data using SQL and JavaScript.
- position is an open source data science company that provides data professionals with cutting-edge tools for code-first data science.
- Kumo.ai is an AI-powered platform that tackles predictive problems in business. The platform works directly with relational data using graph neural networks, a type of AI system that processes data that can be represented as a set of graphs.
- Lamini is an LLM platform for every developer to build a customized private model. It’s easier, faster, and performs better than generic LLM.
New AI model sharing capabilities and data providers
Databricks also offers AI model sharing on the Databricks Marketplace, enabling data consumers and providers to discover and monetize AI models and integrate AI into all data solutions. AI model sharing gives Databricks customers access to best-in-class models that can be applied to their data quickly and securely. Databricks itself curates and publishes open-source models across common use cases such as instructional and text summarization, and optimizes the tuning and deployment of these models on Databricks.
The Databricks Marketplace also welcomes new data providers including financial services leaders such as S&P Global, Experian, London Stock Exchange Group, Nasdaq, Corelogic and YipitData. Healthcare innovators such as Datavant and IQVIA. Geospatial leaders such as Divirod, Accuweather and Safegraph. Data collaboration companies like LiveRamp. Also includes business information services companies such as LexisNexis and ZoomInfo.
availability
The Databricks Marketplace has finished public preview and will be generally available on June 28, 2023. Lakehouse Apps and AI model sharing on the Databricks Marketplace will be previewed next year.
Register for the Data + AI Summit to learn more about the Databricks Marketplace.
About data bricks
Databricks is a data and AI company. More than 10,000 organizations around the world, including Comcast, Condé Nast and over 50% of the Fortune 500, rely on the Databricks Lakehouse platform to unify data, analytics and AI. Databricks is headquartered in San Francisco with offices around the world. Founded by the original creators of Delta Lake, Apache Spark™, and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems. For more information, follow Databricks on Twitter, LinkedIn, and Facebook.
