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How to Export Supabase JSON to Excel (2026 Guide)

Supabase is an incredible open-source Firebase alternative, giving you the power of PostgreSQL with a slick UI. But when your product manager asks for a "weekly report in Excel," the slick UI hits a wall.

Exporting nested JSON data from Supabase to a clean Excel spreadsheet isn't as one-click as it should be.

In this guide, I'll show you 3 authoritative ways to get your data out of Supabase and into Excel—whether you're a developer comfortable with SQL or a founder who just needs the file.

Method 1: The "No-Code" Way (Supabase Dashboard + JsonExport)

Best For: Ad-hoc reports, non-technical team members, and handling nested JSON.

Supabase's built-in CSV export is... basic. It often duplicates rows when handling joined tables or JSONB columns. The better approach is to grab the raw JSON and let a specialized tool flatten it.

Step 1: Export JSON from Dashboard

  1. Log in to your Supabase Dashboard.
  2. Go to the Table Editor (the spreadsheet icon).
  3. Select your table (e.g., users or orders).
  4. Crucial Step: If you have JSONB columns, they will look like {...} in the grid.
  5. Click Export (top right) and choose Download as JSON.
    • Why JSON? CSV exports often break nested JSON objects into unreadable strings.

Step 2: Convert to Excel

Now you have a rows.json file. Don't try to open this manually.

  1. Go to JsonExport.com.
  2. Drag and drop your rows.json.
  3. JsonExport will automatically detect the JSONB columns and "flatten" them into clean Excel columns (e.g., metadata.plan_type, metadata.last_login).
  4. Click Download Excel.

Verdict: The cleanest way to handle complex Supabase data without writing code.

Method 2: The "SQL Power" Way (pgAdmin / SQL Editor)

Best For: specific data subsets or complex joins.

If you only need some users (e.g., "active users signed up last week"), don't export the whole table. Use SQL.

Step 1: Run the Query

In the Supabase SQL Editor:

SELECT 
  id,
  email,
  raw_user_meta_data->>'full_name' as name,
  created_at
FROM auth.users
WHERE created_at > NOW() - INTERVAL '7 days';

Step 2: Export Results

  1. Run the query.
  2. In the Results pane, click CSV (bottom right of the results).
  3. Open that CSV in Excel.

Verdict: Great for simple text data. Fails hard if you try to export arrays or complex JSON objects directly, as Supabase will export them as stringified JSON "{...}" inside the CSV cell.

Method 3: The "Automated" Way (Python Scripts)

Best For: Recurring daily/weekly reports sent via email.

If you need this report every Monday at 9 AM, use the supabase-py client.

from supabase import create_client
import pandas as pd

url = "YOUR_SUPABASE_URL"
key = "YOUR_SUPABASE_KEY"
supabase = create_client(url, key)

# 1. Fetch data
response = supabase.table('orders').select('*, items(*)').execute()

# 2. Flatten and Convert
# The response.data is a list of dictionaries (JSON)
df = pd.json_normalize(response.data)

# 3. Save
df.to_excel("weekly_orders.xlsx", index=False)

Verdict: Requires maintenance, but saves time in the long run.

Common Issues & Troubleshooting

Problem: "My JSONB column is just a string in Excel"

If you use the default CSV export, Excel thinks your JSON object {"id": 1, "name": "foo"} is just text. You can't filter by ID.

  • Fix: Use Method 1. JsonExport parses those strings back into objects and splits them into distinct columns.

Problem: "I have too many rows for the Dashboard"

Supabase dashboard export limits row counts (often 100 or 1000 depending on pagination).

  • Fix: Use Method 2 (SQL) or Method 3 (API) to fetch larger datasets.

Conclusion

  • For quick, accurate exports (especially with JSONB): Download JSON and use JsonExport.
  • For filtered data: Use SQL.
  • For automation: Use Python.

Don't let your data get stuck in the database. Use the right tool for the job.