JSON flattener

Paste nested JSON and instantly flatten it into table-ready keys. Choose your separator, decide how arrays should be handled, and copy or download the result without sending anything to a server.

Key separator

Arrays

Accepts one object or an array of objects. Flattening happens entirely in your browser.

Input JSON

[
  {
    "orderId": "ORD-1024",
    "customer": {
      "id": 481,
      "name": "Ava Patel",
      "plan": "Growth",
      "address": {
        "city": "Austin",
        "state": "TX",
        "country": "US"
      }
    },
    "totals": {
      "subtotal": 249,
      "tax": 20.54,
      "currency": "USD"
    },
    "items": [
      {
        "sku": "analytics-seat",
        "quantity": 3
      },
      {
        "sku": "priority-support",
        "quantity": 1
      }
    ],
    "tags": ["renewal", "vip"],
    "meta": {
      "source": "stripe",
      "sync": {
        "attempt": 2,
        "status": "processed"
      }
    }
  },
  {
    "orderId": "ORD-1025",
    "customer": {
      "id": 482,
      "name": "Liam Chen",
      "plan": "Starter",
      "address": {
        "city": "Seattle",
        "state": "WA",
        "country": "US"
      }
    },
    "totals": {
      "subtotal": 99,
      "tax": 8.91,
      "currency": "USD"
    },
    "items": [
      {
        "sku": "starter-seat",
        "quantity": 1
      }
    ],
    "tags": ["new"],
    "meta": {
      "source": "hubspot",
      "sync": {
        "attempt": 1,
        "status": "queued"
      }
    }
  }
]

Flattened output

What is JSON flattening?

JSON flattening converts nested objects into a single level of keys so the shape is easier to inspect, export, and compare. A nested path like customer.address.city becomes a direct field instead of something you have to drill into manually.

That makes flattened JSON much easier to work with in spreadsheets, CSV exports, SQL staging tables, and debugging workflows where you need a quick view of every available field.

When to flatten nested JSON

Reviewing API responses before mapping them into a table
Preparing event payloads for CSV export or spreadsheet analysis
Inspecting webhook bodies that include deeply nested objects
Comparing records that share a core schema but vary in nested fields
Checking how wide a semi-structured dataset becomes after flattening

How array handling changes the output

Expanded arrays create indexed keys such as items.0.sku and tags.1. This is useful when you want each nested field to be addressable on its own. Preserving arrays as JSON strings keeps them in a single column, which is often cleaner when arrays are long or irregular.

Why separator choice matters

Dot notation is the most familiar default, but underscore and slash separators can be more convenient for spreadsheets, shell tools, or downstream systems that do not treat dots well in field names.

From flattened payloads to instant insights

If you are flattening JSON just to load it into a report or dashboard, Basedash can often skip that prep work. Connect your data source, describe the chart or metric you want, and Basedash writes the query, runs it, and renders the result in seconds.

FAQ

What input shape does this flattener accept?

It accepts a single JSON object or an array of JSON objects. Top-level primitives and mixed arrays are rejected with a friendly validation error.

How are nested arrays handled?

You can either expand arrays into indexed paths like items.0.sku and tags.1, or preserve each array as one JSON string field if that better fits your export workflow.

Does flattening change the values?

No. The structure changes, but the underlying values stay the same. Nested paths are turned into flat keys so the data is easier to inspect, export, and compare.

Can I change the key separator?

Yes. Use dot, underscore, or slash separators depending on the naming style your spreadsheet, script, or warehouse expects.

Is my JSON uploaded anywhere?

No. Everything runs locally in your browser using JavaScript. Your payload never leaves your device.

What is the flattened key count?

The tool reports the number of unique flattened keys discovered across the output records, which is a quick way to understand how wide the flattened schema becomes.