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Documentation Index

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JQ formulas let you apply JQ queries to any JSON column in your table. The result is written into a new column (stored as JSON), giving you full control over nested data without leaving Databar.
JQ formulas are a transformation. They do not consume any credits.

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What is JQ?

JQ is a lightweight command-line language designed for slicing, filtering, and transforming JSON data. It is particularly powerful when you need to dig into deeply nested objects or arrays that enrichment APIs return. If you want to learn more, the official manual is available, though it is fairly technical.

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Generate with AI

You don’t need to learn JQ to use this feature. Databar has a built-in Generate with AI function that can write JQ expressions for you. Just describe what you need in plain language and the AI will generate the expression. LLMs like ChatGPT and Claude are also excellent at generating JQ formulas. Describe your JSON structure and desired output, and they can produce a working expression in seconds.

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How to use

1

Add a JQ Formula transformation

Open your table and add a new transformation column. Select JQ Formula from the list.
2

Select the source JSON column

Choose which column contains the JSON data you want to query.
3

Write the JQ expression

Enter your JQ expression. The query runs per row and the result is stored as JSON in the new column.

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Use cases

ScenarioExample expression
Count specific event types[.events[] | select(.type == "purchase")] | length
Extract a nested value.company.funding.last_round.amount
Build a structured output{name: .full_name, city: .address.city}
Filter an array[.contacts[] | select(.role == "CEO")]

JSON expander

Extract JSON values into separate columns visually.

Excel formulas

Use spreadsheet formulas for simpler column logic.