Databricks, Inc. vs Snowflake Inc.: Strategic Comparison

This in-depth comparison examines Databricks, Inc. and Snowflake Inc. across revenue, market value, business model, competitive positioning, and long-term growth strategy. Whether you are researching Databricks, Inc. on its own, evaluating Snowflake Inc., or weighing the two companies side by side, the breakdown below highlights where each company leads and where the gap between Databricks, Inc. and Snowflake Inc. is widest.

On the headline numbers, annual revenue is $2.6B (FY2025) for Databricks, Inc. and $4.7B (FY2026) for Snowflake Inc., while their respective market capitalizations stand at N/A and $118.0B. Both Databricks, Inc. and Snowflake Inc. are headquartered in United States. Their local markets and applicable rules may still differ.

Databricks, Inc.: Databricks sells a cloud platform where companies store, govern, and analyze their data, then build machine learning models and AI agents on top of it. Based in San Francisco, it grew out of UC Berkeley's AMPLab and the Apache Spark project and later coined the 'lakehouse' idea of running warehouse-style analytics directly on low-cost cloud object storage. Customers such as adidas, AT&T, Bayer, Block, Mastercard, Rivian, and Unilever use it for workloads ranging from ETL pipelines and BI dashboards to fraud models and generative AI applications. Its main rival is Snowflake, with the cloud providers' own data stacks as the other big competitors. The company is headquartered in San Francisco, California.

Snowflake Inc.: Snowflake Inc. (NYSE: SNOW) is a cloud data platform company that lists Bozeman, Montana as its headquarters and operates as a distributed company. Its core idea, separating data storage from the compute used to query it, let customers scale analytics on demand instead of buying fixed hardware from vendors such as Teradata or Oracle. The platform now spans data warehousing, data engineering, applications, data sharing and AI agents, and served 828 customers with more than $1 million in trailing 12-month product revenue as of July 31, 2026.

Databricks, Inc. and Snowflake Inc. pursue distinct approaches to generating revenue, and understanding how each company operates is the foundation of any fair comparison between Databricks, Inc. and Snowflake Inc..

Databricks, Inc. business model: Databricks makes money by charging for compute consumed on its platform, measured in Databricks Units (DBUs). Customers usually sign annual or multi-year committed-spend contracts and then draw them down as their engineers run pipelines, SQL queries, model training, model serving, and AI agents. There is no flat seat fee for most workloads, so revenue rises as data volumes and AI usage grow. Databricks runs on AWS, Microsoft Azure (where it is sold as the first-party Azure Databricks service), and Google Cloud, and customers can often pay for it through existing cloud commitments. Newer products such as Lakebase (serverless Postgres), Genie, and Agent Bricks extend the same consumption model to operational databases and AI agents.

Snowflake Inc. business model: Snowflake runs a consumption-based cloud data platform on top of AWS, Microsoft Azure and Google Cloud. Customers are billed for compute (virtual warehouses, Snowpark, Cortex AI and other services, metered in credits), for storage per terabyte per month, and for data transfer. Most large customers sign multi-year capacity commitments and draw them down as they use the platform; revenue is recognized on consumption, not on contract signing. Professional services and training are a small share of revenue. The Snowflake Marketplace and secure data sharing let customers exchange live data without copying it, which adds workloads and keeps data on the platform.

The durability of a company's moat often decides long-term winners. Here is how the competitive advantages of Databricks, Inc. stack up against those of Snowflake Inc..

Databricks, Inc. competitive advantage: Databricks' advantage comes from its link to open-source software, in particular Apache Spark. Its founders created Spark, the open-source data processing engine used across the technology industry, and Databricks' paid platform is built to run Spark faster and more efficiently. Its Lakehouse architecture lets companies run both standard business reporting and AI models on the same data, which removes the need for separate data systems.

Snowflake Inc. competitive advantage: Snowflake's main advantages are that it runs the same platform across AWS, Azure and Google Cloud, which reduces lock-in to a single hyperscaler, and that storage and compute scale independently, so customers pay only for compute while it runs. Secure data sharing and the Snowflake Marketplace let separate organizations query the same live data without copying it, which creates network effects. Growing support for Apache Iceberg open tables and built-in AI services (Cortex) aims to keep data and AI workloads on the platform.

Future prospects matter as much as current results. The growth strategies below explain how Databricks, Inc. and Snowflake Inc. each plan to expand from here.

Databricks, Inc. growth strategy: Databricks is expanding from analytics into the systems that enterprise AI agents run on. The 2026 funding is earmarked for three products: Lakebase, a serverless Postgres database for agents built on the 2025 acquisition of Neon; Genie, an AI coworker that answers business questions from governed data; and Unity AI Gateway, which routes requests across AI models with governance and cost controls. Acquisitions fill gaps quickly: Panther for security analytics (announced June 2026), Electric for local Postgres sync (August 2026), and Row Zero to add a governed spreadsheet to Genie (September 2026). Alongside this, Databricks keeps pushing its Lakehouse warehousing product to take SQL workloads from legacy and cloud data warehouses.

Snowflake Inc. growth strategy: Under CEO Sridhar Ramaswamy, Snowflake is positioning itself as the data layer for enterprise AI agents. It is adding AI services (Cortex AI, Cortex Agents and Snowflake Intelligence), developer tools (Snowpark, Streamlit, Snowflake Postgres) and open-format support (Apache Iceberg). In 2026 it bought Observe for AI-powered observability, agreed to acquire Natoma for governed agent connectivity via the Model Context Protocol, and acquired TensorStax for agentic data engineering. The raised FY2027 product revenue target of $6.07B (+36%) reflects this push.

A closer look at the financial trajectory of Databricks, Inc. and Snowflake Inc. rounds out the comparison.

Databricks, Inc.: Databricks is private and does not publish full audited financial statements for investors. It reported more than $1.6 billion of revenue for the fiscal year ended January 31, 2024. Its later disclosures are annualized revenue run-rates, not completed fiscal-year revenue: above $5.4 billion in Q4 FY2026 and above $7 billion in Q2 FY2027, the quarter ended July 31, 2026. The August 2026 release said the latest run-rate was growing more than 80% year over year and adjusted free cash flow had been positive over the trailing 12 months; it did not disclose GAAP net income. Within the broader run-rate, Databricks reported more than $1.5 billion for Lakehouse data warehousing and more than $100 million for Lakebase. It reported more than 1,000 customers consuming at over a $1 million annual run-rate and more than 100 at over $10 million. Its announced financing valuations rose from $62 billion in December 2024 to $134 billion in February 2026 and $190 billion in August 2026. Those are private funding-round valuations, not a public market capitalization.

Snowflake Inc.: Snowflake has grown from $96.7M of revenue in fiscal 2019 to $4.684B in fiscal 2026 while remaining GAAP unprofitable, largely because of heavy stock-based compensation. FY2026 revenue grew 29% and the GAAP net loss was $1.332B. Growth accelerated in fiscal 2027: Q2 revenue was $1.55B (+35%), product revenue $1.49B (+37%, the third straight quarter of acceleration), net revenue retention 126%, and non-GAAP operating margin 15.3%. GAAP operating loss for the quarter was $263M. On September 28, 2026 the company announced a $3.5B offering of 0.00% convertible senior notes due 2029 and 2031. Snowflake Inc. is an absolute titan in the cloud computing data warehousing industry, sustaining a massive market valuation generally exceeding $50 billion.