Run queries in the Workbench

Choose SQL to filter rows, Vector to find similar content, Full-text to find words or Graph to follow links. Start with a small query and inspect the returned records. These console examples use local sample data.

SQL: inspect structured rowsCopy Anchor Link

1. Open Workbench and choose SQL.
2. Start from Examples, or write a bounded SELECT against the displayed table.
3. Click Run and inspect Results. Switch the result format to JSON when you need its record structure.

SELECT id, title, category
FROM documents
LIMIT 5;

This query uses the local preview's sample documents. For a live query, use the table names and syntax required by your instance. The SQL reference covers joins, aggregates, limits, and supported statements.

Vector: find similar recordsCopy Anchor Link

Choose Vector, enter the query embedding, set the number of results and optional category filter, then run it. The sample mode uses three dimensions and cosine similarity. A production query must match the stored vectors' dimension and configured distance metric.

For a live embedding workflow, follow the vector quickstart. Use Data Explorer → Embeddings to inspect a sample projection; a three-dimensional visualization does not replace the original embeddings or distance calculation.

Full-text: find matching documentsCopy Anchor Link

Choose Full-text, enter search terms, set the result count, and run. Ranked matches show the fields needed to inspect each hit. In the local preview, the search covers sample document titles and bodies.

For live BM25, boolean, and phrase queries, use the full-text reference and verify that the relevant index exists.

Graph: follow relationshipsCopy Anchor Link

Choose Graph and select a starting node, relationship, direction, and traversal depth. Run the traversal, then select a node or record to inspect its properties. The preview form offers one, two, or three hops over the sample graph.

The live engine's supported Cypher syntax is a separate query surface; use the Cypher guide and graph API reference for those requests.

Natural language: use AskCopy Anchor Link

Natural-language queries use the Ask endpoint. The current Workbench preview does not expose an NL mode. Follow the Ask guide to scope schemas, inspect the compiled plan, and handle the returned rows in an application.

Inspect results before reusing a queryCopy Anchor Link

Choose a result format appropriate to the mode: table, JSON, ranked matches, or graph. Select a record for field details; export CSV when you need the returned records. The browser is not an unbounded data export tool, so keep queries limited and use an SDK for larger retrieval jobs.

Save a useful draft from the toolbar, or reopen a previous input from History. Opening a history entry does not run it. See Workbench in depth for local persistence and query plans for diagnostics.

Engine examples for the shop datasetCopy Anchor Link

These reference examples assume you have created and populated shop.orders and shop.customers with the fields shown. The current quickstart creates a different product table, so it does not prepare these fixtures. Use the corresponding engine endpoint after preparing the required tables; the local preview parser is separate.

SELECT id, customer, amount_cents, status
  FROM shop.orders
 WHERE status = 'paid'
 ORDER BY placed_ms DESC
 LIMIT 10

SELECT customer, COUNT(*) AS orders, SUM(amount_cents) AS total_cents
  FROM shop.orders
 WHERE status = 'paid'
 GROUP BY customer
 ORDER BY total_cents DESC
 LIMIT 8

SELECT o.id, c.name, c.country, o.amount_cents
  FROM shop.orders o
  JOIN shop.customers c ON o.customer = c.id
 WHERE o.status = 'paid'
 LIMIT 10

MATCH (o:orders {id: '01JTRX1H4Q9P0N2WMX0F5JZ001'})-[:customer]->(c)
RETURN c.name, c.country
LIMIT 10

which countries spent the most on paid orders

table:field one or more query terms

shop.orders:notes rush delivery
^^^^^^^^^^^ ^^^^^ ^^^^^^^^^^^^^
   table    field     terms

shop.orders:notes rush delivery