Dataiku vs Hugging Face

By valuation, Hugging Face is the larger company at $4.5B versus $3.7B — a 1.2x difference. Size can also be measured by team: Dataiku employs 1000+ people while Hugging Face has 250 employees.

Dataiku has raised more in total funding at $1B, compared to Hugging Face's $395M — a gap of $605M. Combined, the two companies have completed 7 known funding rounds.

Dataiku leads with an Awaira Score of 90/100, while Hugging Face sits at 82/100. That 8-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Dataiku was founded by Florian Douetteau in 2013. Hugging Face was founded by Clement Delangue in 2016. Visit each company's profile on Awaira for a full founder biography.

Dataiku: Dataiku builds a collaborative data science and machine learning platform that enables data teams, business analysts, and AI engineers to build, deploy, and monitor machine learning models within a single unified environment. The Paris-founded company platform covers the full ML lifecycle from data preparation and feature engineering through model training, deployment, and governance, supporting both code-based and visual, low-code workflows to serve teams of varying technical sophistication.\n\nThe company raised over $1 billion in total funding including a $400 million Series E led by Tiger Global and ICONIQ Growth, reaching a valuation of $3.7 billion. Dataiku counts over 600 enterprise clients globally including Unilever, GE, Sanofi, and the US Army Corps of Engineers, and reports thousands of active practitioners using the platform daily. The company has offices in New York, London, Paris, Singapore, and Sydney, reflecting a global enterprise sales motion that has made it one of the largest pure-play ML platform vendors in the world.\n\nDataiku competes in the data science platform market against Databricks, SAS, KNIME, and H2O.ai. Its differentiation is the breadth of user personas it serves within a single platform, allowing collaboration between data scientists, ML engineers, and business domain experts without requiring separate tools. The company is considered one of Europe most successful enterprise AI software exports, with the majority of its revenue generated outside France and a valuation that places it among the top independent AI platform companies in the world. Hugging Face: Hugging Face is an AI platform company founded in 2016 that has become a central hub for the machine learning community. The company provides open-source libraries, pre-trained models, and collaborative tools for natural language processing and machine learning development. Its flagship offering, the Transformers library, enables developers to access and fine-tune state-of-the-art models for tasks including text classification, translation, summarization, and question-answering. The Hugging Face Model Hub hosts over 700,000 open-source models contributed by researchers and practitioners globally, making it a primary resource for model discovery and sharing. The company also offers inference APIs, AutoTrain for automated model training, and enterprise solutions for organizations deploying models in production. Hugging Face has achieved a $4.5 billion valuation with $395 million in total funding as of its Series D stage. The platform serves a diverse user base ranging from individual researchers to major technology companies. Its competitive positioning centers on democratizing access to advanced AI models through open-source initiatives and community-driven development. The company generates revenue through hosted inference services, enterprise features, and AutoTrain premium offerings. Growth has been driven by increasing demand for accessible AI tools and the model-sharing economy expansion. Hugging Face operates the largest open-source model repository, positioning it as infrastructure for the AI development ecosystem rather than a consumer application.

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

Dataiku has about 1000+ employees; Hugging Face has about 250. 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 Dataiku and Hugging Face compete in ML Platform, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.