Snowflake vs. Databricks: The $1.25 Billion PostgreSQL Battle for AI Agent Supremacy
Brief Overview: Two data giants are making strategic moves to dominate the AI agent infrastructure market through major PostgreSQL acquisitions. Snowflake’s $250 million purchase of Crunchy Data and Databricks’ $1 billion acquisition of Neon represent a fundamental shift in how B2B software companies are preparing for the era of autonomous AI agents. These deals highlight the critical importance of database infrastructure in powering next-generation AI applications and signal an accelerating consolidation trend in the B2B and SaaS industry.
Snowflake’s Crunchy Data vs. Databricks’ Neon: A Strategic Database Battle
The Acquisitions at a Glance
Snowflake ➝ Crunchy Data
- Deal value: ~$250 million
- Crunchy Data generates over $30 million in annualized revenue
- Timeline: Expected to close in the next couple of weeks
- Announced at Snowflake Summit 2025
- Focus: Enterprise-ready PostgreSQL with security and compliance for government and large businesses
Databricks ➝ Neon
- Deal value: ~$1 billion
- Neon has more than 18,000 customers
- Founded in 2021, raised $129.6 million previously
- Focus: Serverless PostgreSQL optimized for AI agents
Strategic Motivations: The AI Agent Revolution
Both acquisitions center on the explosive growth of AI agents, but with different approaches:
Databricks’ Agent-First Strategy Over 80 percent of the databases provisioned on Neon were created automatically by AI agents rather than by humans, highlighting how “the era of AI-native, agent-driven applications is reshaping what a database must do.” Databricks CEO Ali Ghodsi noted that “pretty much every customer we have wants to leverage agents.”
Snowflake’s Enterprise-Focused Approach Snowflake’s strategy targets enterprise customers and government agencies. As Vivek Raghunathan, senior vice president of engineering at Snowflake, explained: “The vision here is that Snowflake Postgres will simplify how developers build, deploy and scale agents and apps. With that in mind, it was important to acquire a company that was not just engineered for quick experimentation.” Snowflake is “tackling a massive $350 billion market opportunity and a real need for our customers to bring Postgres to the Snowflake AI Data Cloud.”
Market Context: The PostgreSQL Rush
PostgreSQL is now the most popular database, according to the 2024 Developer Survey by Stack Overflow, outpacing the open source MySQL format and databases from Microsoft, MongoDB and Redis. This popularity stems from PostgreSQL’s versatility—it can “handle geospatial, time series, JSON and vector database workloads.”
The competitive dynamics are intense: Snowflake also looked at buying Neon last year but walked away, showing how competitive this space has become. Now both companies are joining tech giants including Nvidia and OpenAI in pursuing clients who want to build their own AI agents.
Snowflake’s Broader AI Strategy
Snowflake’s momentum in AI is accelerating. The company reported more than 5,200 business customers using its AI capabilities weekly and achieved quarterly revenue topping $1 billion for the first time in Q1 2025—exceeding analyst expectations. This acquisition builds on previous AI investments, including the 2023 purchase of Neeva, a generative AI search startup.
Implications for SaaS and B2B Software
1. The Agentic AI Infrastructure Race
According to Gartner, by 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024. These acquisitions position both companies for this massive shift, where AI agents operate at “machine speed” and traditional database provisioning often becomes a bottleneck.”
2. Consolidation Accelerating
In the first half of 2024 alone, software M&A transactions in the U.S. rose to 30.8%, and experts predict a record number of SaaS mergers and acquisitions (M&A) in 2025. These database acquisitions represent a broader trend of “tech giants buying data startups to bolster their underlying database offerings that power AI agents.”
3. Infrastructure Becomes Competitive Advantage
For companies still planning their AI roadmap, this acquisition signals that database infrastructure decisions should prioritize serverless capabilities that can adapt quickly to unpredictable AI workloads. The ability to spin up a fully isolated Postgres instance quickly is becoming essential for AI-native applications.
4. The Economics of AI Workloads
AI agents demand “a cost structure that scales precisely with usage” and “full separation of compute and storage keeps the total cost of ownership for thousands of ephemeral databases proportional to the queries they actually run.”
Market Positioning: Enterprise vs. Developer-First
The stark difference in valuation—$250M vs $1B—reflects different market positions and strategies:
- Neon’s premium: Reflects its serverless architecture, proven AI agent adoption, and developer-friendly approach with 18,000+ customers
- Crunchy Data’s value: Lies in enterprise compliance, government relationships, and battle-tested infrastructure for regulated industries
Crunchy Data’s roughly 100 employees bring deep expertise in serving large businesses and government agencies with PostgreSQL infrastructure, complementing Snowflake’s enterprise focus.
The Bottom Line
These acquisitions signal a fundamental shift in B2B software infrastructure where companies aren’t just buying databases—they’re acquiring the foundational technology for AI-driven applications. The deal validates that even advanced data companies need specialized serverless database capabilities to support AI agents that create and manage databases programmatically.
For B2B and SaaS companies, this means database architecture decisions are no longer just technical choices—they’re strategic business decisions that will determine which companies can effectively deploy AI agents at scale. With the SaaS market projected to reach $299 billion by 2025 and AI becoming core to business operations, controlling the database layer that powers AI agents represents a critical competitive moat in the evolving landscape of enterprise software.
