Databricks Marketplace Grows with Lakehouse-Native Apps and AI Model Sharing

The digital age has brought new tools to a variety of industries, in particular the data science and engineering space with the emergence of a platform called Databricks. Earlier today, Databricks announced a major growth in their Marketplace that brings a new set of applications, specifically designed to run natively on the Databricks Unified Analytics Platform (UA) and the recently announced Databricks Lakehouse.

Databricks, a company that offers commercial platforms for data engineering and machine learning developers, is expanding their Lakehouse capabilities with faster, secure data access and more sophisticated analytic capabilities like AI model sharing. This expansion specifically includes Lakehouse-native apps that act as on-demand cloud services, allowing users to quickly and easily access data science services, machine learning, and predictive analytics.

The Databricks Marketplace also now features a variety of third-party apps that have added new solutions to help reduce the infrastructure needed to add model-sharing capabilities. These verified applications offer the necessary integration to take a model from development to deployment and enable organizations to share models securely and quickly.

Theplatform also now features tools specifically designed to help developers optimize deployments in the cloud. For example, a new billing estimator feature helps estimate how much customers can expect to pay when using Marketplace apps. This feature is available for all apps that are available for purchase on the Databricks Marketplace.

Finally, an additional tool now in the Databricks Marketplace offers enhanced interoperability and security features for machine learning and data analytics.The tool allows users to easily share, manage, and control machine learning and analytics models in an interoperable manner among multiple users.

Overall, this impressive expansion of the Databricks Marketplace offers customers easier and faster access, as well as better security and optimized deployments in the cloud. With the addition of these new apps and tools, Databricks continues to expand the capabilities of its platform for everyone from novice data professionals to experienced machine learning engineers.