ARLINGTON, Va., Sept. 9, 2021 /PRNewswire/ -- Stardog, the leading Enterprise Knowledge Graph (EKG) technology platform provider, today announced that it has been recognized as a Sample Vendor in five separate 2021 Gartner Hype Cycle reports. More specifically, Gartner identified Stardog in the following Hype Cycle reports:
- Hype Cycle for Data Management, 20211
- Hype Cycle for Enterprise Information Management, 20212
- Hype Cycle for Application Architecture and Integration, 20213
- Hype Cycle for Digital Government Tech, 20214
- Hype Cycle for Life Science Research and Development, 20215
Stardog believes its inclusion in these Gartner reports further affirms the company's momentum and commitment to helping customers leverage knowledge graph technology to speed time to insight, accelerate data lake productivity, and modernize analytics to gain a competitive advantage. Through a unique combination of graph, virtualization, and inference technologies, Stardog's knowledge graph platform is the key ingredient to transforming an existing data and analytics infrastructure into a data fabric - a modern technology approach that is being hailed as the next generation data management solution. Weaving together data from internal silos and external sources, data fabrics create a seamless network of information and support the entire connected enterprise.
Gartner defines data fabric as "…an emerging data management design for attaining flexible and reusable data integration pipelines, services and semantics". The report further states that, "A data fabric leverages both traditional and emerging technologies in enterprise architectural design and evolution. It is composable and supports flexibility, scalability, and extensibility in an infrastructure used by humans or machines across multiple data and analytics use cases."2
"We believe our recognition in these Gartner reports validates the significance of our Enterprise Knowledge Graph platform as the key enabling ingredient to transforming our customer's existing data infrastructure into a highly effective data fabric," said Kendall Clark, founder and CEO of Stardog. "Digital transformation demands rapid insight from messy real-world data, but traditional data integration platforms simply can't keep up with growing complexity, frequently changing business requirements, and greater demand for curated datasets."
Additional Resources
- Learn how Stardog Enterprise Knowledge Graph Platform can help you
- Explore Stardog blog
- Try Stardog Free
Please Tweet: #knowledgegraph platform provider @StardogHQ recognized as a sample vendor in 5 @Gartner_inc #HypeCycle Reports #datafabric #dataintegration
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About Stardog
Stardog was founded in 2015 on the vision of powering the connected enterprise. Stardog's Enterprise Knowledge Graph technology platform turns data into knowledge to enable more effective digital transformations. With Stardog, customers reduce data preparation timelines by up to 90 percent by transforming enterprise data infrastructure into a comprehensive end-to-end data fabric. Industry leaders including BNY Mellon, Bosch, and NASA use Stardog to create a flexible data fabric that can support countless applications. Stardog is a privately held, venture-backed company headquartered in Arlington, VA. For more information, please visit www.stardog.com or follow them @StardogHQ.
1 Gartner, "Hype Cycle for Data Management, 2021," Philip Russom, Donald Feinberg, July 27, 2021. (Gartner subscription required)
2 Gartner, "Hype Cycle for Enterprise Information Management, 2021", Donna Medeiros, Andrew White, August 2, 2021. (Gartner subscription required)
3 Gartner, "Hype Cycle for Application Architecture and Integration, 2021", Eric Thoo, Massimo Pezzini, July 15, 2021. (Gartner subscription required)
4 Gartner, "Hype Cycle for Digital Government Technology, 2021", Alia Mendonsa, July 21, 2021. (Gartner subscription required)
5 Gartner, "Hype Cycle for Life Science Research and Development, 2021" Jeff Smith, Michael Shanler, July 19, 2021. (Gartner subscription required)
SOURCE Stardog
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