Snowflake and Databricks are absolutely comparable firms. Whereas every positions itself a bit in a different way, each present information storage, processing and governance in a cloud context. Each are holding buyer conferences this week, and each are searching for methods to assist prospects construct generative AI and different clever functions on high of the information saved in these platforms.
If that wasn’t clear earlier than, it grew to become much more obvious this week when Databricks introduced it was buying MosaicML for a cool $1.3 billion. That’s some huge cash for a startup, even a properly capitalized one like Databricks. The transfer got here weeks after the corporate introduced it was releasing Dolly, an open-source LLM, and one other acquisition in AI governance instrument Okera.
Snowflake introduced final month that it was shopping for Neeva, giving it a search instrument and a few high-end AI engineering expertise. The corporate additionally purchased Streamlit final 12 months, which lets firms construct functions from the information saved in Snowflake, and on Wednesday, it introduced a brand new container service and partnership with Nvidia, giving prospects a method to construct generative AI functions and run them on Nvidia GPUs.
All of those strikes (and others) are designed with one factor in thoughts: to make use of the information saved in these providers as gasoline for machine studying fashions, particularly massive language fashions. Each firms wish to assist prospects benefit from all this information saved on their platforms.
Nvidia’s VP of enterprise computing, Manuvir Das, talking within the context of Wednesday’s partnership announcement with Snowflake, sees the transfer towards extra sensible use of the information as a logical development for Snowflake.
“The truth that Snowflake is now transferring on this subsequent step the place they’re saying, OK, not solely can you retain your information right here and do type of the plain information processing issues on it, however that is the place the place you’ll be able to construct all of the functions that drive your organization as a result of your information is true right here. That’s a really highly effective factor,” Das informed TechCrunch+.
Equally, Databricks is more and more seeing itself as a spot the place you can’t solely retailer information and do the assorted information duties related to that, however you can too be half of a complete information stack, the place you construct functions on high.
This week’s MosaicML acquisition was a part of this broader technique to put the information to work in an AI context, stated Ray Wang, founder and principal analyst at Constellation Analysis. That’s one thing that was exhausting for Databricks to do, even with Dolly.
“The AI angle is all about making it straightforward to accumulate, handle, practice and deploy LLMs with ease,” Wang stated.
Each firms are clearly transferring exhausting towards AI via acquisitions, partnerships and product growth. However what does that imply from a possible income perspective for the way forward for these firms, one among which is already public and one which absolutely will probably be there finally?
Enterprise AI demand just isn’t illusory
Databricks and Snowflake are each rising in a short time. The most recent data from Databricks signifies that in its most up-to-date fiscal 12 months, it generated greater than $1 billion in income, rising at greater than 60%. Snowflake’s outcomes are equally spectacular, posting $623.6 million in income in its most up-to-date quarter, up 48% in comparison with the year-ago interval.