The modern data stack needs a reimagined metadata management platform
Acryl Data’s vision is to bring clarity to your data through its next generation multi-cloud metadata management platform. The technology is based on LinkedIn DataHub and Apache Gobblin - two successful open source projects incubated at LinkedIn, and battle-hardened in production at scale at major enterprises.
Our Story
Founded by the leaders that created projects like LinkedIn DataHub and Airbnb Dataportal, Acryl Data provides a developer-friendly modern data catalog built on top of a next generation Metadata Platform to bring clarity to data in all enterprises.The last decade of innovation in the data tools has led to increasing ability to capture, store and process data at all levels of volume, variety and velocity. Companies have greatly benefited from data-driven decision making based on the freshest data and deriving business value using AI-enabled data products.
An unintended consequence of this innovation has been the increasing fragmentation due to specialized data tools. With the explosion of different kinds of data -- from online databases, to streaming data, to data at rest, to features, models, dashboards and metrics -- data professionals and executives are struggling to realize value from data effectively. Meanwhile, central data teams find themselves chronically understaffed to cater to the needs of all the data professionals at the company, while implementing global policies consistently across the organization. Tech giants like LinkedIn and Airbnb have solved this problem over multiple years of evolution and investment, but most organizations don’t have access to these highly specialized teams and technology. Even when the technology is open sourced as in the case of LinkedIn DataHub, companies may not have the resources to run and operate this at scale and integrate it effectively into their operational data fabric to power critical workflows.
We believe that data-driven organizations need a reimagined developer-friendly data catalog to tackle the diversity and scale of the modern data stack. Our goal is to provide the most reliable and trusted enterprise data graph to empower data teams with best-in-class search and discovery and enable continuous data quality based on DataOps practices. This allows central data teams to scale their effectiveness and companies to maximize the value they derive from data.
