BreezoMeter vs Databricks

Databricks has a disclosed valuation of $134B, while BreezoMeter'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 BreezoMeter's $21M — a gap of $20.2B. Combined, the two companies have completed 8 known funding rounds.

Databricks leads with an Awaira Score of 93/100, while BreezoMeter sits at 42/100. That 51-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

BreezoMeter was founded by Ran Korber in 2014. Databricks was founded by Ali Ghodsi in 2013. Visit each company's profile on Awaira for a full founder biography.

BreezoMeter: BreezoMeter provides AI-powered environmental data APIs covering air quality, pollen, weather, and wildfire risk, aggregating data from government monitoring stations, satellite imagery, and IoT sensors and applying machine learning models to produce street-level resolution environmental intelligence that application developers and enterprises integrate into health, insurance, and mobility products. The Haifa company delivers real-time and forecast environmental data at hyperlocal granularity that government monitoring networks cannot match.\n\nThe company raised approximately $21 million in venture funding and was acquired by Google in 2022, integrating its environmental data capabilities into Google Maps, Google Search, and Google Nest products. Prior to acquisition, BreezoMeter had built API customers including insurance companies for climate risk underwriting, asthma and respiratory health applications for personalised air quality alerts, and HVAC companies for air filtration product recommendations tied to local pollution levels.\n\nBreezoMeter competed in the environmental data and climate intelligence market alongside AirVisual (IQAir), PurpleAir, and government air quality data portals. The acquisition by Google reflected the strategic value of hyperlocal environmental data as an enrichment layer for mapping, local search, and home automation products where air quality and pollen information enhances the relevance of location-based recommendations. The combination of machine learning interpolation and sensor fusion to generate street-level environmental data from sparse monitoring networks represented a technically defensible approach that aligned with Google investment in location data quality. 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 1 year of extra runway. BreezoMeter didn't arrive until 2014. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

BreezoMeter 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 BreezoMeter and Databricks compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.