Superb AI vs Databricks

Databricks has a disclosed valuation of $134B, while Superb AI'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 Superb AI's $42.8M — a gap of $20.2B. Combined, the two companies have completed 9 known funding rounds.

Databricks leads with an Awaira Score of 93/100, while Superb AI sits at 60/100. That 33-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Superb AI was founded by Hyun Kim in 2018. Databricks was founded by Ali Ghodsi in 2013. Visit each company's profile on Awaira for a full founder biography.

Superb AI: Superb AI provides an AI data labelling and dataset management platform that combines annotation tools with AI-assisted labelling automation, quality assurance workflows, and dataset analytics for computer vision AI development teams. The Seoul and San Francisco company Suite product covers image, video, and 3D point cloud annotation across bounding box, segmentation, keypoint, and polygon annotation types, targeting autonomous vehicle, robotics, and AI product companies that require high-quality labelled datasets at scale.\n\nThe company raised approximately $70 million in a Series C round from investors including SoftBank Ventures Asia, Kakao Ventures, and Madrona Venture Group. Superb AI has expanded its platform beyond annotation tooling to include dataset management, model evaluation, and AI-assisted label suggestion that reduces the manual effort required per annotation through model-assisted pre-labelling followed by human review.\n\nSuperb AI competes in the AI data platform market against Scale AI, Labelbox, Encord, and V7, as well as annotation services providers that offer managed labelling workforce services. Its Korean origin has provided access to the automotive and manufacturing AI market in Korea, where companies including Hyundai, Kia, and LG Electronics are significant purchasers of AI training data and annotation services. The company dual San Francisco and Seoul presence reflects its strategy of serving both Korean enterprise clients and the global AI development market from a single platform. 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 5 years of extra runway. Superb AI didn't arrive until 2018. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Superb AI has about 100-500 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 Superb AI and Databricks compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.