Is Snowflake’s Crunchy Data Acquisition a Game-Changer in the AI Data Platform Race?

Is Snowflake’s Crunchy Data Acquisition a Game-Changer in the AI Data Platform Race

Analyst(s): Brad Shimmin
Publication Date: June 4, 2025

Snowflake’s Crunchy Data acquisition signals a major bet on combined operational and analytical workloads as an enabler of enterprise-grade AI infrastructure. The move brings Snowflake into closer competition with Databricks and other cloud data giants as the market for AI-ready database solutions heats up.

What is Covered in this Article:

  • Snowflake’s Crunchy Data acquisition and its position relative to recent database M&A moves
  • The strategic importance of Postgres and open-source database technology for AI workloads
  • Impact on Snowflake’s product roadmap and developer ecosystem
  • Guidance, market reaction, and implications for enterprise technology buyers

The News: Snowflake announced its intention to acquire Crunchy Data, a leading enterprise-grade PostgreSQL cloud technology provider, for approximately $250 million. The transaction, unveiled at Snowflake’s annual Summit, will add roughly 100 Crunchy Data employees to Snowflake and power a new offering: Snowflake Postgres. This follows rival Databricks’ recent $1 billion acquisition of Neon, marking an industry trend of major data platform vendors buying Postgres and next-generation database leaders for AI agent and application workloads. Crunchy Data, founded 13 years ago, serves Fortune 500 companies, government agencies such as the U.S. Department of Homeland Security, and large ISVs.

The acquisition will enable Snowflake to deliver a FedRAMP-compliant, developer-friendly, and AI-ready Postgres solution within the Snowflake Data Cloud, targeting organizations requiring secure, scalable databases for mission-critical AI applications. The new Snowflake Postgres product is set for private preview and will bring Crunchy Data’s robust scaling, operational governance, and performance tooling to a broader enterprise client base. Commenting on the news, Vivek Raghunathan, SVP of Engineering at Snowflake, said, “Our vision is to deliver the world’s most trusted and comprehensive data and AI platform to our customers. Today’s announcement of our proposed acquisition of Crunchy Data represents another reason why Snowflake is the ultimate destination for all enterprise data and AI workloads.”

Is Snowflake’s Crunchy Data Acquisition a Game-Changer in the AI Data Platform Race?

Analyst Take: Snowflake’s acquisition of Crunchy Data is a defensive and offensive maneuver in the rapidly escalating battle for leadership in cloud-native data intelligence platforms. Like Databricks’ purchase of Neon and Salesforce’s Informatica deal, Snowflake is betting on the convergence of operational and analytical workloads as espoused in open data lakehouse architectures to drive the next wave of AI agentic application development. The $250 million price tag, while far less than Databricks’ recent $1 billion for Neon, reflects both the urgency and the premium price vendors are paying to deliver enterprise-grade Postgres solutions that can underpin AI and application workloads at scale.

Strategic rationale: The move brings Snowflake Crunchy’s 100-person team of Postgres experts and gives the company instant clout within the vibrant Postgres open source community. It also brings Snowflake a proven technology that meets strict enterprise and government standards (e.g., FedRAMP compliance). Most importantly, it allows Snowflake to capitalize on developers’ heavy preference for Postgres—the world’s most popular operational database.

Competitive context: This deal solidifies a new front in the data, AI, and analytics wars, with Snowflake and Databricks now more directly contending to be the default data intelligence cloud for operational and analytical AI workloads. By integrating enterprise-grade Postgres, Snowflake can more readily sell to customers wanting to build AI agents and mission-critical apps. The launch of Snowflake Postgres, which leverages Crunchy Data’s open-source know-how, scaling capabilities, and operational governance, will be key in attracting existing Postgres installations through the opportunity to leverage PostgreSQL alongside Snowflake’s well-established data warehouse platform.

Ecosystem implications: Customers such as UPS, SAS, Moneytree, Blue Yonder, and LandingAI already use Crunchy Data or Postgres as the backbone for operational data. Snowflake’s platform now becomes a viable destination for these workloads, offering “out-of-the-box” metrics, robust scaling, and developer-ready interfaces, all essential for the growing class of agentic AI business applications. This broadens Snowflake’s addressable market and sets the stage for new ecosystem partnerships and integrations.

Market impact: By moving decisively to own Postgres talent and IP, Snowflake is making a clear statement: the battle for enterprise AI will be won not only with large language models and analytics alone but with the ability to supercharge these technologies through secure, scalable, open source-powered cloud native software infrastructure. For buyers, this increases the urgency to re-evaluate their operating database strategy, especially as major SaaS and cloud players continue to embrace top-tier Postgres providers. The data intelligence platform’s bar for the competition is now much higher.

The Database M&A Surge

In the last two quarters, the market has seen a sharp uptick in major cloud and AI vendors’ acquisitions of database and data engineering companies. Databricks’ $1 billion buyout of Neon and Salesforce’s acquisition of Informatica reflect the strategic necessity of controlling core data infrastructure. This trend rapidly consolidates choice for enterprise buyers and intensifies the battle between Snowflake, Databricks, AWS, Salesforce, SAP, and Google for database workloads beyond analytics.

The Strategic Role of Postgres in AI Apps

Postgres has emerged as the de facto standard among open-source relational databases, with 49% of all developers using it (per company-reported data). The flexibility, SQL compatibility, and strong community support of Postgres make it a prime foundation for building a wide array of applications requiring transactional and analytical processing. With its acquisition of Crunchy Data, Snowflake gains mature tooling and a proven operational backbone, accelerating the rollout of Snowflake Postgres as an enterprise-grade offering. Customers in regulated industries and high-scale environments gain a secure, compliant path to migrate or build Postgres workloads in the cloud.

Impact on Snowflake’s Developer Ecosystem

A central driver of this deal is to attract and retain developer mindshare. By fusing Crunchy Data’s developer-friendly implementation of Postgres with the Snowflake platform, the company shortens the time to value for organizations seeking to build, deploy, and scale AI agents alongside and increasingly within business apps. Snowflake now offers a full-stack experience that appeals to data engineers seeking performance and scale, and to app dev teams needing mature APIs, tooling, and security. This positions Snowflake to capture workloads previously hosted on-premises or in competing cloud environments, and may accelerate its partnerships with ISVs and SaaS vendors.

Guidance, Preview, and Market Reaction

Snowflake has indicated that Crunchy Data’s team and technology will be integrated rapidly, with a private preview of Snowflake Postgres available soon. While financial details beyond the acquisition value are not public, the reaction from the market has been largely positive. However, the broader open source community will certainly exercise caution until Snowflake proves its commitment to supporting the Postgres project. Customers and partners (e.g., Blue Yonder, LandingAI) are already referenced as early adopters. Investors are watching for execution risk in integrating the two platforms and the pace at which Postgres workloads migrate to the Snowflake Data Cloud.

What to Watch:

  • Regarding Snowflake’s direct contributions to the PostgreSQL open-source project and community, will the Crunchy Data engineers continue to be active, visible contributors, and will Snowflake foster open collaboration, or will contributions diminish or become primarily internal?
  • Related to the previous bullet, how will Snowflake maintain full compatibility and leverage truly open-source PostgreSQL, or will it introduce proprietary extensions or “community licenses” that could fragment the ecosystem? Customers will be watching closely to see how the company manages licensing and feature set of “Snowflake Postgres” compared to vanilla PostgreSQL.
  • Snowflake will look to leverage this acquisition to drive adoption rate and migration patterns of existing PostgreSQL users to “Snowflake Postgres.” Given that, how will developers and enterprises, particularly those in regulated industries, trust Snowflake’s offering for their mission-critical OLTP and AI workloads, and will it accelerate their move to the Snowflake Data Cloud?

See the complete press release on this acquisition on Snowflake’s website.

Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum as a whole.

Other insights from Futurum:

Previous Analysis: Snowflake Q4 FY2025 Earnings Report

Databricks’ Neon Acquisition and Market Impact

Snowflake and the AI Landscape Amid Databricks Competition

Author Information

Brad Shimmin

Brad Shimmin is Vice President and Practice Lead, Data and Analytics at Futurum. He provides strategic direction and market analysis to help organizations maximize their investments in data and analytics. Currently, Brad is focused on helping companies establish an AI-first data strategy.

With over 30 years of experience in enterprise IT and emerging technologies, Brad is a distinguished thought leader specializing in data, analytics, artificial intelligence, and enterprise software development. Consulting with Fortune 100 vendors, Brad specializes in industry thought leadership, worldwide market analysis, client development, and strategic advisory services.

Brad earned his Bachelor of Arts from Utah State University, where he graduated Magna Cum Laude. Brad lives in Longmeadow, MA, with his beautiful wife and far too many LEGO sets.

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