Google Sheets row limit: 20 million cells, explained

According to Google Drive Help, a spreadsheet created in or converted to Google Sheets can hold up to 20 million cells or 100 MB. The cap applies to the whole spreadsheet, counted across all tabs. There is no fixed row limit.

Because the cap counts cells, the rows you can fit depend on how many columns you use. A narrow table can hold millions of rows, while a wide export runs out much earlier. Every cell in every tab draws from the same 20 million cell pool.

Google does not publish a maximum column count. Each column you add lowers the rows that fit under 20 million cells, and if the cells hold long strings, you can hit the 100 MB cap first.

• 50,000 characters per cell on conversion: when an Excel file is converted to Google Sheets, any cell with more than 50,000 characters is removed.
• Connected Sheets pivot tables: up to 200,000 rows.
• Connected Sheets extracts: up to 500,000 rows or 5 million cells.

If an import fails while your row and column math stays under 20 million cells, check the 100 MB size cap. Long text such as raw JSON logs fills it quickly.

Excel uses a fixed grid per worksheet instead of a cell budget shared across the file. A single Excel worksheet holds up to 1,048,576 rows by 16,384 columns.

With a narrow table of 5 or 10 columns, Google Sheets fits more rows than an Excel worksheet: up to 4,000,000 or 2,000,000 at the cell limit, against Excel's hard stop at 1,048,576. At 20 columns Google Sheets drops to 1,000,000 rows for the entire file. At 100 columns it tops out at 200,000 rows across all tabs, while an Excel worksheet still allows 1,048,576.

Open the CSV, TSV, JSON, JSONL or Parquet file in rows.page instead. DuckDB-WASM reads it inside your browser, so the file stays on your machine unless you click Share, and opening files is free with no account.

The grid has no row limit and loads rows in pages of 100 as you scroll. CSV, TSV, JSON and JSONL files open up to 1.5 GB per browser tab. A bigger CSV, TSV or JSONL file loads partially with the note "Loaded the first N rows: the file is X, more than the browser can hold." Parquet is not held to the 1.5 GB check because DuckDB reads it in place.

You can filter with country:NL or price:>20, check each column's histogram and sort the whole dataset. rows.page does not open .xlsx or .xls files, edit cells or run spreadsheet formulas, so save Excel files as CSV first.

A public link opens the same way: put it after https://rows.page/, as in https://rows.page/https://example.com/data.csv. If the host blocks cross-origin requests, the rows.page proxy fetches up to 100 MB within 30 seconds and stores nothing.

If you still need the data in Google Sheets for charts or formulas, aggregate it in rows.page first. Type a DuckDB SQL query that starts with SELECT, WITH or FROM into the filter box; the table is always named data.

SELECT
  country,
  status,
  count(*) AS total_rows,
  sum(amount) AS total_amount
FROM data
GROUP BY country, status
ORDER BY total_rows DESC

1. Open your CSV, TSV, JSON, JSONL or Parquet file in rows.page.
2. Run a GROUP BY query, or filter the table down to the rows and columns you need.
3. Click Export and choose CSV to save the current view or SQL result.
4. Import that smaller CSV into Google Sheets with File > Import.

SQL results return up to 1,000,000 rows, and filtered views export every matching row. The CSV is comma-delimited UTF-8 without a BOM, and text cells starting with =, +, -, @, a tab or a carriage return get a leading apostrophe so spreadsheets don't run them as formulas.

If the data already lives in BigQuery, skip the CSV and use Connected Sheets to query it from your spreadsheet, within its limits of 200,000 rows for pivot tables and 500,000 rows or 5 million cells for extracts.