Can I connect a graph database like Neo4j to iDBQuery?
Not as a native graph connection — iDBQuery is built for SQL and relational data, and graph databases like Neo4j use their own query model. To analyse graph data, export the nodes and relationships to CSV or expose them through an API, and iDBQuery will query that with cited answers.
iDBQuery natively connects to SQL databases, spreadsheets, files, documents, REST APIs, and SQL data warehouses. Graph databases such as Neo4j model data as nodes and relationships and query it with graph languages like Cypher, so they aren't a native SQL connection — but you can still analyse graph data with iDBQuery through a truthful, tabular path.
Common approaches:
- Export to CSV — export the nodes and relationships (or the specific query results you care about) to CSV, and point iDBQuery at those tables.
- Expose through an API — if a service returns graph query results as JSON over REST, connect iDBQuery to that API as a source.
Once the data is tabular in iDBQuery's model, you get plain-language questions, generated SQL, charts, and cited answers. This works well for the aggregate, tabular questions people usually bring to reporting — counts, sums, and breakdowns over entities and their connections — rather than deep multi-hop traversals, which are best left to the graph engine itself.
The upside is blending: join graph-derived tables with your relational databases and spreadsheets in one live model, so you can answer questions that mix relationship data with business records. For anything that truly needs graph traversal, keep using your graph database for that part and bring the summarised results into iDBQuery for the reporting layer.
Updated 2026-06-22