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In the run-up to its annual Data + AI summit, enterprise data lakehouse vendor Databricks has announced its Marketplace service will soon play host to next-gen applications capable of running natively inside the lakehouse, and play host to ready-to-use models, shared and monetized by third parties.
The move will give Databricks’ enterprise customers more resources to put their data into use and, ideally, drive value and business growth. The Ali Ghodsi-led company gears up to make its Marketplace generally available on June 28.
How will lakehouse apps help?
Since its preview last year, Databricks Marketplace has been serving as an open platform that enables data consumers and providers to discover, share and monetize data products like datasets, notebooks and dashboards — without any platform dependencies, complicated ETL or expensive replication.
With the addition of lakehouse apps, the company is expanding this ecosystem to include third-party apps that leverage next-gen technologies, such as large language models, to unlock the value of data.
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Previously, software vendors struggled to get such applications to customers’ data, owing to the complexity of obtaining the necessary security, legal and commercial approvals as well as clearing the hurdles to securely access the data.
Lakehouse apps address all these challenges, giving vendors a way to take their products to potential customers with the same security, privacy and compliance controls as Databricks.
Once a Databricks user picks an app from the marketplace, it will run directly on their lakehouse instance and securely integrate with the data stored there. It could also use and extend Databricks services — all without data ever leaving the customer’s instance.
To start off, the company is working to bring multiple lakehouse apps to the marketplace, including those from Retool, Lamini, Posit and Kumo AI. More vendors are expected to join as the platform evolves.
Model sharing for simpler access to AI
Just like lakehouse apps, Databricks Marketplace will enable easy access to AI models developed and provided by third parties — catering to a variety of use cases and domains.
“For instance, a provider built a domain-specific model — say a natural language model to detect clinical phrases specific to healthcare. Now, they can put that model on marketplace so customers can take it and use it on top of their data, without the need to move the data outside of their Databricks instance,” Joel Minnick, VP of product marketing at Databricks, told VentureBeat.
This way, the customer gets the model they need right where their data lies, while the provider is able to monetize their work, reaching thousands of enterprises on Databricks.
Availability on Databricks Marketplace
As of now, there’s no fixed timeline for the availability of lakehouse apps and AI model sharing on Databricks Marketplace. The company said that it is working on the offerings and will launch them in preview in the coming year.
It is also adding new data providers to its marketplace, including S&P Global, Corelogic, YipitData, Datavant, IQVIA, Accuweather, Safegraph and LiveRamp.
Notably, Databricks’ main rival Snowflake also offers a marketplace with data, data services and applications from leading data and solution providers. However, it doesn’t yet host AI model-sharing capabilities.
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