Snowflake has acquired Crunchy Data for [openai_gpt model="gpt-4o-mini" prompt="Summarize the content and extract only the fact described in the text bellow. The summary shall NOT include a title, introduction and conclusion. Text: The rivalry between Snowflake and Databricks has taken an intriguing turn, extending its reach into the burgeoning realm of PostgreSQL. This shift signifies a strategic pivot as both companies seek to capitalize on the growing demand for robust database solutions tailored for AI applications.
In a bold move, Snowflake has recently acquired Crunchy Data for 0 million, while Databricks has made headlines by purchasing Neon for a staggering billion. These acquisitions are not merely about expanding their portfolios; they represent a calculated effort to harness the capabilities of PostgreSQL in the context of AI-driven data management.
Snowflake's acquisition announcement, detailed in a blog post, highlights PostgreSQL as a favored choice among developers, owing to its flexibility, cost efficiency, and inherent AI features, such as vector support (pg vector). The open-source nature of PostgreSQL, coupled with its vibrant ecosystem, further enhances its appeal.
“We’re tackling a massive 0 billion market opportunity and a real need for our customers to bring Postgres to the Snowflake AI Data Cloud,” stated Vivek Raghunathan, Snowflake’s SVP of engineering.
Why are the Giants Betting on PostgreSQL?
“PostgreSQL’s ecosystem and extensions are growing fast. More people now know this database better than any other. pgvector gave it a big push,” remarked Arpit Bhayani, creator of DiceDB, when asked about PostgreSQL's rise as the preferred database for AI-native applications.
Snowflake Postgres builds upon the company's earlier foray into transactional data with Unistore, which integrates transactional and analytical workloads within a single system. By enhancing native PostgreSQL support, Snowflake Postgres aims to provide enterprises with a production-ready solution for transactional applications that require compatibility with PostgreSQL.
The open-source relational database PostgreSQL has seen a surge in popularity, surpassing MySQL as the most favored database among developers, according to Stack Overflow’s 2023 and 2024 Developer Surveys. Its capabilities in handling geospatial data (via PostGIS), time series data (via TimescaleDB), JSON, and vector embeddings (via pgvector) position it as an ideal choice for AI applications.
In a recent LinkedIn post, senior data engineer Avinash S emphasized that these acquisitions signify more than just the addition of another database. He views them as a strategic bet on PostgreSQL as the backbone of the AI-native era, particularly in its serverless and cloud-native forms. “Imagine AI agents spinning up databases for every real-time task or experiment, then discarding them. Traditional databases can’t handle this ‘disposable’ scale. Serverless Postgres delivers the rapid provisioning, elasticity, and cost-efficiency that AI agents desperately need to work autonomously and at speed,” he elaborated.
“It’s not just agentic. Because many people are talking about it and using it, it has become the de facto standard,” Bhayani noted, although he cautioned that the assumption of AI agents creating databases may be overly optimistic.
Factorial Advisors echoed this sentiment in a blog post, asserting that Databricks’ acquisition of Neon aligns with its broader ambition to construct a unified data intelligence platform. “With over billion in financing and a recent billion valuation, Databricks has the financial muscle to keep acquiring,” they wrote, highlighting previous acquisitions like Tabular ( billion) and MosaicML (.3 billion). Neon addresses the increasing demand for databases that operate at ‘agentic speed’ while maintaining cost-effectiveness through pay-as-you-go models.
These strategic moves position both Snowflake and Databricks to challenge hyperscalers like AWS, Microsoft Azure, and Google Cloud, which offer managed PostgreSQL services seamlessly integrated with their AI stacks.
Neon vs Crunchy Data
Established in 2012, Crunchy Data specializes in providing a comprehensive, production-ready PostgreSQL solution that encompasses backups, high availability, disaster recovery, connection scaling, and monitoring. This service supports mission-critical deployments across cloud, on-premises, and hybrid environments.
Snowflake has asserted that its new offering, Snowflake Postgres, will facilitate the integration of transactional Postgres data into its platform, thereby accelerating innovation and granting developers enhanced agility, visibility, and control to construct reliable AI agents and applications more swiftly.
Crunchy’s expertise ensures that Postgres-powered applications can operate natively on Snowflake without necessitating code rewrites. Developers stand to gain from built-in connection pooling, performance metrics, and logging, simplifying the process of building and managing scalable applications.
Conversely, Databricks CEO Ali Ghodsi emphasized that frontier LLMs have been trained on extensive datasets from the Postgres open-source ecosystem, rendering AI agents inherently adept at utilizing Neon, which is built on PostgreSQL. He highlighted that Databricks and Neon share a foundational technical infrastructure and a commitment to open source, noting that Databricks originated the Apache Spark project at UC Berkeley, the same institution where PostgreSQL was developed.
Ghodsi pointed out that OLTP databases, a 0 billion market, remain largely dominated by legacy products. With Neon, Databricks aims to disrupt this landscape by crafting the most developer- and AI agent-friendly database platform available. Since Neon became generally available last year, the proportion of databases created by AI agents has surged from around 30% to over 80%, indicating a significant shift towards AI-driven database creation.
The rush towards PostgreSQL is palpable, with Snowflake and Databricks actively acquiring niche providers to enhance their offerings. This trend transcends mere database proliferation; it signifies a readiness for AI, real-time data processing, and the evolving demands of large-scale enterprises.
These acquisitions also reflect a broader consolidation trend within the data and AI infrastructure market. Recent transactions, such as Salesforce’s billion acquisition of Informatica, ServiceNow’s purchase of Data.World, and Alation’s acquisition of Numbers Station, illustrate how companies are racing to establish comprehensive AI-ready platforms. According to Bhayani, much of this activity is driven by the imperative to acquire customers and specialized expertise." max_tokens="3500" temperature="0.3" top_p="1.0" best_of="1" presence_penalty="0.1" frequency_penalty="frequency_penalty"] million, while Databricks has purchased Neon for billion. Both companies are focusing on PostgreSQL to enhance their database solutions for AI applications. PostgreSQL has gained popularity among developers, surpassing MySQL as the most favored database, due to its flexibility and features like vector support. Snowflake aims to integrate PostgreSQL data into its platform with Snowflake Postgres, while Databricks seeks to leverage Neon to create a developer-friendly database platform. The trend towards PostgreSQL is part of a broader consolidation in the data and AI infrastructure market, with companies acquiring specialized expertise to build comprehensive AI-ready platforms.
