Databricks Targets AI Database Market with $1B in New Funding
CEO Ali Ghodsi: 'There's a new user. The user is not human.'
Welcome to the Cloud Database Report. I’m John Foley, a long-time tech journalist, including 18 years at InformationWeek, who also worked in strategic comms at Oracle, IBM, and MongoDB. Connect with me on LinkedIn.
I’ve been on the road for the past two weeks, first in Salt Lake City on business, then to Dublin for a visit. While in Ireland, I took the train to Limerick to see The Saw Doctors, a favorite band that has been playing its unique style of Irish folk-rock since 1986. Remember the year because I will to come back to it.
[As a break from the routine, I’ve included below a music video of The Saw Doctors that was released just last year. It’s a good soundtrack that was filmed in the Irish countryside. I hope it brings a smile.]
The same day I landed back in New York, Databricks announced it had raised another $1 billion, an investment that will go toward its recently unveiled database system, Lakebase, and its new agent-building platform, Agent Bricks.
This could be a game-changing development in the database market. Databricks, now valued at more than $100 billion, is throwing its considerable weight, resources, and influence into a market that is ripe for disruption. The database stalwarts—AWS, Google Cloud, Microsoft, Oracle—are surely paying attention.
What are the implications? There’s an old Irish saying that hindsight is the best insight to foresight.
Hindsight:
Databricks has long been a player in data management, with a core competency in analytics, data intelligence, and data science. I included Databricks on the Cloud Database Report’s Top 20 when it was published in 2022. So they already have a foothold.
Databricks has been a leading proponent of the data lakehouse architecture, which is an evolution and blending of data warehouses and data lakes. The appeal of lakehouses includes the simplicity of a unified data platform, efficiencies in storage and data pipeline processes, support for both raw data and transformed/formatted data, and serving as a data repository both analytics and AI.
Insight:
In June, Databricks CEO Ali Ghodsi revealed on LinkedIn that—despite the company’s marketing mantra of “data intelligence”—he really thinks of Databricks as an AI database. That acknowledgement, which I wrote about in a blog post, now carries greater significance given the company’s plans to invest in Lakebase, which it describes as “a new type of operational database (OLTP), built on open source Postgres, and optimized for AI Agents.”
Note the reference to Postgres serving as the foundation for a new type of operational database. Postgres (like The Saw Doctors) has been around since 1986, so it’s a remake of a legacy database into a modern AI database.
What’s most significant is that Lakebase (in public preview) can support both analytics—Databricks’ forte—and operational data. That’s important because AI agents need to act and respond in real-time. (Lakebase isn’t a vector database. Rather, vector data types are supported via an integrated vector search service.)
Foresight:
Ghodsi pegs the database industry’s total addressable market (TAM) at $105 billion. That’s in line with the $100 billion I reported last year. Which puts the database market at roughly the same size as the analytics market and half the size of the data storage market, according to Perplexity.
Ghodsi recognizes that the database market is in the throes of change as new capabilities are required to support AI data and AI agents. Taking that a step further, AI agents are autonomously creating databases. “There’s a new user. The user is not human. It’s an AI agent, and if we just double down on making that user persona successful, that’s the wedge to disrupt that TAM,” Ghodsi told Julie Bort at TechCrunch.
Optimized for AI agents
Databricks—which was not among the Top 10 in database market share in 2024, according to Gartner—has just fired a shot across the bow of the industry leaders. Ghodsi said to TechCrunch: “The database market is $105 billion of TAM, of revenue, sitting there, kind of unaffected in the last 40 years.”
Translation: Ghodsi sees an opportunity to drive innovation—and, in doing so, get a bigger piece of the TAM pie that in his words is “sitting there” for the taking.
The other piece of this is Agent Bricks, a new platform-as-a-service (in beta) for building enterprise AI agent systems. Initial use cases are an Information Extraction Agent, Knowledge Assistant Agent, Multi-Agent Supervisor, and Custom LLM Agent, with more planned.
I wasn’t able to find a detailed description of how Lakebase and Agent Bricks will work together, but given the data dependencies of agentic AI, my expectation is there will be integration and synergy between them.
Here’s how Ghodsi explained Lakehouse and Agent Bricks not long ago when they were introduced.
More recently, Databricks has disclosed plans to acquire Tecton for low-latency data engineering. According to Reuters, Ghodsi explained it as a real-time building block for AI agents.
RIP database categories
It’s clear that the way CIOs and CTOs are looking to transform business data into business value is going through a massive rethink, sparked first by GenAI and now advancing to agentic AI. With that comes the idea that a new tech stack is needed, which is the opportunity that Databricks and others are after, i.e. Snowflake + Crunchy Data and Salesforce + Informatica.
Relational, NoSQL, and other tried-and-trusted DBMSs will continue to have their place, but disruption is afoot. MongoDB says, “Database Categories Are Dead.”
The categories may be dead or dying, but data management is more important than ever in this new age of AI.
