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Based in San Mateo, California, Datometry develops database virtualization technology that enables enterprises to migrate from legacy data warehouses to modern cloud databases without rewriting their underlying applications. The company's flagship Hyper-Q platform facilitates real-time interoperability between existing software and modern databases, effectively reducing typical enterprise migration timelines from several years to a matter of weeks. Datometry serves a broad customer base of Fortune 500 companies across North America, Europe, and Asia, delivering up to 90% cost reductions and accelerating data transitions by up to 4 times. The firm's core migration technology was recently acquired by Snowflake, prompting key executives, including the chief executive officer and chief technology officer Michael Duller, to join the acquiring organization. Additionally, the company has received board-level backing from venture capital investors such as Redline. Datometry was founded in 2013 by Mike Waas.
Datometry has raised $33.0M across 3 funding rounds.
Datometry has raised $33.0M in total across 3 funding rounds.
Datometry has raised $33.0M in total across 3 funding rounds.
Datometry's investors include Celesta Capital, Celesta, Insight Partners, LiveOak Venture Partners, Mayfield, Redline Capital, Amarjit Gill, Acorn Pacific Ventures, Dell Technologies Capital.
Datometry has raised $33.0M across 3 funding rounds. Most recently, it raised $17.0M Series B in February 2020.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Feb 1, 2020 | $17M Series B | Celesta Capital | Celesta, Insight Partners, LiveOak Venture Partners, Mayfield, Redline Capital, Amarjit Gill, Acorn Pacific Ventures, Dell Technologies Capital | Announced |
| Oct 1, 2019 | $6M Series B | — | Celesta | Announced |
| Jun 1, 2017 | $10M Series A | Redline Capital | Insight Partners, LiveOak Venture Partners, Mayfield, Acorn Pacific Ventures, Dell Technologies Capital | Announced |
Datometry is a San Francisco-based technology company founded in 2013 that develops SaaS solutions for database system virtualization, enabling enterprises to migrate legacy data warehouses to modern cloud platforms like Snowflake, Databricks, Microsoft Fabric, and Google BigQuery without rewriting applications.[1][2][3][4][5][6] Its flagship products—Hyper-Q, qInsight, and qShift—deliver up to 80% savings in time, cost, and risk by translating queries in real-time, providing workload insights, and automating schema generation, serving Fortune 500 and Global 2000 customers across industries to accelerate cloud-native data management.[1][2][3][5][6] Recently, Snowflake acquired Datometry's migration technology, integrating it into SnowConvert AI to speed migrations up to four times faster and cut costs by 90%, with key team members like CEO Mike Waas joining Snowflake.[4][6]
Datometry was founded in 2013 by Mike Waas, who serves as CEO, alongside CTO Michael Duller and other experts addressing the frustrations of costly, years-long data warehouse migrations that often exceeded budgets.[2][4][6] The idea emerged from recognizing that traditional replatforming—costing tens of millions and posing high business risk—could be disrupted through middleware that makes legacy applications interoperable with cloud databases in real-time, eliminating SQL rewrites or API changes.[2][6] Early traction came from Fortune 500 clients in North America, expanding to Asia and Europe, with Hyper-Q as the core innovation flipping the script on migrations that previously went "sideways."[2][5][6]
Datometry rides the surge in cloud data warehouse adoption and AI-driven analytics, where legacy systems like Teradata create migration barriers that incumbents exploit as "defensive moats."[4][5][6] Its timing aligns with exploding demand—projected $10B+ migration market—enabling enterprises to become AI-ready quickly amid vendor lock-in challenges.[2][5] By virtualizing the database layer, it influences the ecosystem as a standard for interoperability, accelerating shifts to platforms like Snowflake and fostering a future where no application connects directly to databases without such fabric.[2][4][6]
With Snowflake's acquisition of its core technology, Datometry's innovations will embed deeply into the AI Data Cloud, supercharging migrations and positioning it as middleware for all enterprise workloads.[4][6] Trends like rising AI data needs and fixed-fee economics will drive broader adoption, evolving its influence from migration accelerator to ubiquitous data fabric.[2][5][6] This positions Snowflake-enhanced Datometry to outpace competitors, empowering global enterprises to unlock cloud-native advantages without legacy drag—just as it set out to fix migrations gone wrong.
