
Query Streams
7.7#3 in data virtualization softwareFrom $15 a monthFree planWebAPILinuxmacOS
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| Fact | Query Streams | Stardog |
|---|---|---|
| Company headquarters | LinkedIn lists the headquarters as Memphis, Tennessee, United States. | The current LinkedIn company profile lists headquarters in New York, New York, while Stardog’s own footer lists an Arlington, Virginia address. |
| Connectors | The connector directory lists 53 sources, including 11 database engines, 27 hosted or managed services, 8 business APIs, and 7 file and folder types. | Stardog connects to more than 80 enterprise sources and offers a generic REST connector for bespoke applications. |
| Documentation depth | The documentation includes step-by-step Windows, macOS and Linux installation, troubleshooting, connector setup and MCP connection guides. | Official documentation includes administration, querying, virtualization, inference, constraints, tutorials, API references, examples and application-building guidance. |
| Founded | LinkedIn lists Query Streams as founded in 2025. | 2006 |
| License | The service and Agent are proprietary commercial software licensed for internal business use; the terms prohibit copying, modification, reverse engineering and redistribution. | Stardog Free is proprietary, licensed software and the pricing FAQ explicitly says it is not open source. |
| Purpose | Query Streams provides governed access to databases and APIs for spreadsheets, AI clients, apps, and scheduled data syncs through an outbound-only Network Agent. | Stardog connects enterprise data into a semantic layer for AI, analytics, search, and applications. |
It suits teams that want to share governed database and API results with spreadsheet users, AI clients or scheduled integrations. The Free tier may fit limited query traffic; larger needs can use paid plans starting at $15 a month.
Stardog suits organizations that need to unify data across cloud and on-premises sources for analytics, AI, search, or applications. It is also relevant to teams that need graph-based data modeling, standards-based querying, and deployment options spanning managed cloud and self-hosting.