Stardog recently announced the release of Stardog Cloud, a cloud-native Enterprise Knowledge Graph that connects data in the cloud and on-prem environments. Stardog Cloud is deployed as a managed service and unifies data across the enterprise ecosystem based on its meaning and context. Stardog’s knowledge graph is based on a combination of graph, virtualization, and inference. Stardog is dubbing its release of Stardog Cloud as an ‘industry first.’ Stardog expanded its Series B funding round to $11.4 million in May.
Stardog’s data virtualization capabilities enable organizations to leave data within existing data sources and silos and query it as it resides and then perform complex queries across silos. Semantic models rationalize the meaning between legacy applications in a scalable way. It also supports multiple apps and data models in order to bring context to data and support the decision-making process. The Stardog Inference Engine connects data without having to rely on explicit key matching. It utilizes machine learning and inferencing regardless of the data domain or subject area and then uses the information to discover new relationships.
In a media statement about the release, Stardog CEO Kendall Clark said: “A connected enterprise is one where data, no matter where it is stored, is connected at the compute layer as opposed to the storage layer. Stardog helps attain this goal for organizations since it supports every line of business in the enterprise to make decisions based on contextual knowledge and build a reusable, resilient data fabric that can make knowledge-based and proactive rather than reactive.”
Learn more about Stardog Cloud or read Connected Enterprises Care about Meaning, Not about Data in the company’s blog.
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