Databricks Hosts Data + AI Summit, Unveils Suite Of AI Tools For Customers

Key takeaways

• Databricks has announced a boost to its existing Lakehouse platform, complete with new AI and governance capabilities
• The announcement comes as competitor Snowflake reveals a new partnership with Nvidia and the expansion of its work with Microsoft
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• A Databricks IPO is still uncertain, despite the company being the eight most valuable start-up in the world, as the company looks to build out its AI offering instead

Databricks and Snowflake are hosting their respective summits this week, with a string of announcements unveiled at each event. Databricks has revealed its new AI-augmented Lakehouse IQ platform, while Snowflake confirmed it was partnering with Nvidia to help customers build their own AI models.

It’s been good news for Snowflake’s stock this year as it benefits from the AI halo effect, but investors are still left wondering when Databricks, worth $33 billion, might take the plunge and go for its IPO soon. A string of AI-focused acquisitions for the data storage company suggests that reality might be a way off. Here’s the lowdown.

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What is Databricks and the Data + AI Summit?

Data storage and AI company Databricks isn’t pulling punches at its latest summit, as it looks to become one of the top companies for enterprise AI.

At the summit, Databricks revealed it’s augmenting its existing Lakehouse data platform with new AI, natural language processing and data governance features. Lakehouse IQ will allow users to develop their own generative AI models, with the idea that the Lakehouse platform handles data, AI models and governance all on one platform to make the process more efficient.

What does that actually mean? Databricks has created a generative AI platform that takes all of a business’ info, like mission statements and data usage patterns, then outputs a far more accurate and relevant AI chatbot for the organization. Databricks also plans to make Lakehouse IQ available as an API, with plans to integrate the tech into open-source libraries.

In his keynote speech at the event, Databricks CEO Ali Ghodsi said the AI-powered Lakehouse platform “gives you control over your intellectual property”. He also predicted that in five years’ time, every company “will be an AI and data company” and being in control of their own data and models would win ahead of third-party services.

Could Databricks go for an IPO?

Databricks is worth $33 billion as of its most recent valuation from October last year. This is actually a small haircut from its $38 billion valuation back in 2021 when the tech market was at its peak, but Databricks is still the eighth most valuable start-up in the world, even with the lower valuation.

Regarding the figures, Databricks looks very healthy: it saw sales jump 60% in its fiscal year ending in January, generated $1 billion in revenue, and its data warehousing product passed the $100 million mark in annualized recurring revenue this April.

Despite this, Ghosdi says there aren’t any immediate plans for an IPO as, he said in an interview with Bloomberg, “right now the markets are shut down”. There’s no denying the reality: IPO activity has dropped off a cliff after the golden times of 2021, when 397 IPOs in the U.S. were worth a collective $142 billion. In 2023 so far, there have only been 49 IPOs worth a total of $8.3 billion.

Instead, the company is focusing on building its AI capabilities – a savvy move, given Wall Street’s love affair with the buzzy new tech. Databricks recently announced two new purchases: it’s acquiring AI storage and serving systems start-up Rubicon for an undisclosed amount and taking over generative AI start-up MosaicML for $1.3 billion. Rubicon focuses on building storage systems for AI, while MosaicML builds high-end large language models.

Databricks’ competitor might have the edge

Databricks isn’t the only one hosting a big summit this week. Its competitor Snowflake has also made a string of AI-focused announcements at the 2023 Snowflake Data Summit. Forging ahead with its grand plans to become the leading AI data storage and analysis company, Snowflake revealed that it’s partnering with computer chip titan Nvidia; the partnership will let Snowflake customers build their own AI models using their own data.

Each Snowflake model will be built and stored on Snowflake’s data cloud, while the company will use Nvidia chips and AI software to power the building, training and tweaking of the models.

At the news, Snowflake stock gained 3.9% in premarket trading and the stock has climbed nearly 7% over a five-day period to reach $183.85. The share price has soared 35.6% since the start of the year.

Nvidia’s share price, which reached a milestone earlier this year as it became the first trillion-dollar chip maker, gained 0.5% at the announcement. Nvidia has had an incredible run this year, having spent the last decade building the foundations of its generative AI suite, seeing a 187% lift to its share price in 2023. Snowflake’s partnership with the chip-making giant will certainly give Databricks a run for its money.

And that’s not the only partnership it has – Snowflake also confirmed this week it was expanding its existing partnership with Big Tech titan Microsoft, which has been an early frontrunner in the AI race, to bring generative AI to Snowflake’s Data Cloud suite. The move will allow Snowflake and Microsoft Azure data scientists to integrate the two products further.

The bottom line

It’s clear that while the public sees the immediate opportunity with AI through chatbots like ChatGPT and Bard, that’s just the tip of the iceberg when it comes to enterprise use cases. Databricks is looking to capitalize on the gap in the market now, but it faces stiff competition from the likes of Snowflake.

Ultimately, this competitiveness means customers will win as the need for generative AI heats up. Investors holding out hopes for a Databricks IPO in the future should keep a weather eye on the outcome of this new tech to see if it’s hot air or the real deal to transform Databricks’ long-term future in the data sector.

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