MindsDB Query Engine vs Virtual Data Platform
MindsDB Query Engine
github.comVirtual Data Platform
virtualdataplatform.comSide by side
| Figure | MindsDB Query Engine | Virtual Data Platform |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 1 | 1 |
| Spec score · Data Federation Software | 8.1 (#7) | 7.5 (#16) |
| Audience | The project describes itself as a standalone open-source query engine that can give AI agents live, SQL-queryable access to data and semantic search. | The product is developed for organizations seeking secure, governed access to enterprise data across systems and network boundaries. |
| Founded | 2018 | 2021 |
| Headquarters | Berkeley, California, United States | Gröbenzell, Germany |
| Integrations | The README names databases, warehouses, applications, and files as source categories and gives PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery, S3, and Slack as examples. | Listed integrations include SAP, Snowflake, Salesforce, Workday, SQL Server, SharePoint, ODBC, OData, Oracle, PostgreSQL, BigQuery, and Dynamics 365. |
| Purpose | MindsDB Query Engine provides semantic search over data through SQL and connects to more than 200 data sources. | Provides real-time access to enterprise data across systems, networks, and organizations without replicating it into a warehouse or lake. |
Plans
In their own words
MindsDB Query Engine
MindsDB Query Engine provides SQL access to connected data sources and semantic search, including for AI agents that need live, queryable data. It connects to more than 200 sources and runs federated queries against them in place, using one SQL dialect without copying data or using ETL pipelines. Listed source examples include PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery, S3, and Slack. Users can work in an HTTP SQL editor or connect clients such as DBeaver and SQLAlchemy through MySQL and PostgreSQL wire protocols. For unstructured content, knowledge bases pair an embedding model with a vector store and, optionally, a reranking model. Hybrid search combines vector similarity with BM25 keyword matching. Projects organize work, views preserve cross-source transformations, and scheduled jobs run SQL at intervals. Deployment options include Docker and PyPI installation. The engine is available for Linux, web, API, and self-hosted use. The free plan is listed at free; MindsDB Core uses the Elastic License 2.0, and some repository directories have separate licenses.
Virtual Data Platform
Virtual Data Platform (VDP) provides live access to enterprise data across systems, networks, and organizations without copying it into a warehouse or lake. Queries run against source systems, and results are combined in an in-memory sandbox for each user. Its low-code Modeler creates reusable Virtual Datasets from Functions, Code Files, Models, and Value Lists. Users can work with the data through Excel, Power BI, Python, R, and MCP-capable AI assistants. Listed integrations include SAP, Snowflake, Salesforce, Workday, SQL Server, SharePoint, ODBC, OData, Oracle, PostgreSQL, BigQuery, and Dynamics 365. Users sign in with Microsoft Entra ID, and queries apply source-system permissions under the requesting user’s identity. The maker describes outbound-only gateway connections, TLS on every connection, encrypted payloads, and results held in memory rather than saved to disk. It describes the service as GDPR-aligned and hosted in the EU on Microsoft Azure, while making no certification claims today. A Dedicated tier offers a dedicated backend cluster and Azure Private Endpoints.