Cervest vs Databricks

Databricks has a disclosed valuation of $134B, while Cervest's valuation is not publicly available, making a direct size comparison difficult. Databricks employs 6,000 people.

Databricks has raised more in total funding at $20.2B, compared to Cervest's $32M — a gap of $20.2B. Combined, the two companies have completed 7 known funding rounds.

Databricks leads with an Awaira Score of 93/100, while Cervest sits at 45/100. That 48-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Cervest was founded by Iggy Bassi in 2016. Databricks was founded by Ali Ghodsi in 2013. Visit each company's profile on Awaira for a full founder biography.

Cervest: Cervest builds a climate intelligence platform that quantifies climate risk for physical assets including agricultural land, commercial real estate, and infrastructure, using AI models that integrate climate science projections with asset-level data to produce probabilistic risk scores across multiple climate scenarios and time horizons. The London company targets institutional investors, insurers, and corporate treasury teams seeking to quantify physical climate risk in their portfolios.\n\nThe company raised approximately $32 million including a Series A round with investors including Astanor Ventures, Alumni Ventures, and the Future Planet Capital fund. Cervest built its EarthScan product as a SaaS platform delivering climate risk analytics for millions of individual assets, compatible with financial reporting frameworks including TCFD and SFDR that require climate risk disclosure from institutional investors. The platform covers risk categories including flood, drought, heat, wildfire, and storm surge across global geographies.\n\nCervest competes in the physical climate risk analytics market alongside Jupiter Intelligence, The Climate Service, and Verisk Climate, as well as large financial data providers including Moody ESG Solutions and S&P Sustainable. Regulatory pressure on financial institutions to disclose climate-related physical risks under TCFD and forthcoming mandatory climate disclosure regimes represents the primary demand driver for the company products. The market is growing rapidly as regulators in Europe, the UK, and North America formalise climate risk reporting requirements for banks, insurers, and listed companies. Databricks: Databricks is an AI and data platform founded in 2013 that provides a unified analytics workspace for data engineering, data science, and machine learning. The company developed Databricks Lakehouse, which combines data lake and data warehouse capabilities, built on Apache Spark technology. Its platform enables organizations to process large-scale data, build machine learning models, and deploy AI applications through a single interface. The company offers several core products: Databricks SQL for analytics, Databricks Machine Learning for model development, and Databricks Jobs for workflow automation. The platform supports multi-cloud deployment across AWS, Azure, and Google Cloud. Databricks serves enterprises across various industries, with customers including organizations in financial services, technology, and healthcare sectors. As of its latest funding round, Databricks has raised $11.2 billion in total funding and maintains a valuation of $134 billion, positioning it among the highest-valued private AI and data companies. The company achieved Series J funding status, indicating significant capital accumulation and investor confidence. Databricks competes with platforms like Snowflake, Teradata, and cloud-native data solutions from major hyperscalers. The company's growth trajectory reflects strong market demand for integrated data and AI infrastructure, driven by increasing enterprise adoption of machine learning and data-driven decision-making. Databricks unified the traditionally separate data warehouse and data lake approaches through its Lakehouse architecture, creating a single platform for analytics and AI workflows.

Databricks got there first, launching in 2013 — that's 3 years of extra runway. Cervest didn't arrive until 2016. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Cervest has about 1-50 employees; Databricks has about 6,000. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Cervest and Databricks compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.