DataHub (by Acryl Data), a leading open-source metadata platform, announced it has raised $35 million in Series B funding led by Bessemer Venture Partners. This latest funding round brings the company’s total to $65 million, enabling accelerated development of its context management platform, which provides discovery, observability, and control across data, AI models, and AI agents.
DataHub’s open-source offering is used by over 3,000 organizations globally, including Apple, Chime, Foursquare, Netflix, Optum, Pinterest, and Slack. Over the last two years, the company has experienced sixfold growth in selling the enterprise managed service, DataHub Cloud.
DataHub’s event-driven architecture provides real-time visibility as a significant advantage over legacy vendors. And its extensibility and scalability are stand-out benefits along with a full spectrum of deployment options, from single-node to cloud-hosted, hybrid, and decentralized deployments. This architectural advantage has led to competitive wins against established players, with customers citing DataHub’s superior performance, unified capabilities across discovery and data observability, and the ability to support AI governance needs.
Along with the funding, the company is rebranding itself to just be known as DataHub. The name change accurately reflects its core mission of building a metadata platform that is powering AI-ready data systems at scale.
Value proposition: Enterprises are facing critical challenges in accessing, maintaining reliability, and securing their data and AI supply chain. And organizations struggle with “missing context” that prevents both humans and machines from effectively working with data.
1.) Data consumers cannot easily find relevant datasets.
2.) Data engineers lack visibility to prevent disruptions when making changes.
3.) Governance teams struggle to track sensitive data access.
For AI systems, this context gap is even more critical. So AI models need to know when new data is available for refreshing predictions, which enterprise data is trustworthy, and how to analyze schema changes automatically. DataHub addresses this challenge by providing a real-time metadata platform that brings order to data and AI chaos, enabling machines to interact with an organization’s data assets with complete context awareness.
What the funding will be used for: DataHub will use the new capital to:
1.) Invest in the DataHub open source community, which has grown 50x to over 13,000 members
2.) Accelerate R&D with focus on AI governance and context management capabilities
3.) Scale go-to-market operations to meet growing enterprise demand
4.) Build enterprise-grade customer success capabilities
New board member: As part of the investment, Lauri Moore of Bessemer Venture Partners will join DataHub’s board of directors.
KEY QUOTES:
“Rapid adoption of AI in the enterprise is revealing the significance of comprehensive visibility, reliability, and trust across their data and AI ecosystem—far beyond traditional data cataloging to a machine-scale world where AI agents become the power users of data. DataHub is uniquely positioned to lead this new category of AI & data context management with our architecture built for extreme scale, performance, and real-time machine-scale automations.”
Swaroop Jagadish, CEO and co-founder of DataHub
“With the shift toward business-critical AI and customer-facing predictive applications, enterprises need robust metadata management to ensure AI systems can reliably work with data. DataHub provides the context that AI systems need to understand data lineage, quality, and semantics—enabling organizations to unlock the full potential of their AI investments.”
Shirshanka Das, CTO and co-founder of DataHub
“Metadata is the missing link enabling organizations to transition from human-scale data analytics to machine-scale enterprise AI. DataHub is uniquely positioned to address this critical need with its schema-first, event-oriented architecture that brings data and model context and control into a single pane of glass. Enterprises will use DataHub to develop AI ‘safely’ – in a way that respects user privacy and ensures people, models, and agents only access the data and context when and where they are supposed to – without compromising velocity.”
Lauri Moore, Partner at Bessemer Venture Partners
