Excel vs Google Sheets: JSON Export and API Capabilities Compared

Spreadsheets remain the world’s most widely used database. However, as business intelligence tools shift towards real-time API integrations, the ability to convert grid data into nested JSON (and vice versa) has become a mandatory requirement for data engineers.

While both Microsoft Excel and Google Sheets are dominant players, they approach JSON parsing and REST API integration from completely different architectural paradigms.

This guide compares their capabilities, script execution environments, and API constraints.

Google Sheets: The Web-Native Paradigm

Google Sheets was built for the web. Consequently, its ecosystem is highly optimized for interacting with web protocols, REST APIs, and JSON payloads.

The Power of Apps Script

The primary advantage of Google Sheets is Google Apps Script (GAS). Because GAS is fundamentally based on Javascript (V8 engine), it inherently understands JSON.

If a developer needs to fetch a JSON payload from an external API, they can execute standard Javascript operations:

function fetchJsonData() {
  const response = UrlFetchApp.fetch('https://api.example.com/data');
  const json = JSON.parse(response.getContentText());
  // Instantly map json.items to the spreadsheet grid
}

Google Sheets as a Read-Only API

Google Sheets allows you to publish a document to the web and interact with it as a headless database. By modifying the feed URL, developers can pull live sheet data as a raw JSON feed.

Furthermore, by deploying an Apps Script as a "Web App", developers can write custom doGet() and doPost() endpoints, effectively turning Google Sheets into a free (albeit rate-limited) CRUD API.

Microsoft Excel: The Enterprise Processing Engine

Excel approaches JSON entirely differently. It is not designed to be a web endpoint; it is designed to ingest massive amounts of data from external sources and process it locally.

Parsing JSON with Power Query

Excel relies on Power Query (M-code) to handle JSON. If you connect Excel to a REST API, Power Query intercepts the JSON payload and provides a visual interface to drill down into nested objects and expand arrays into relational columns.

While incredibly powerful for data modeling, M-code is notoriously steep in its learning curve compared to simple Javascript.

The Limits of VBA

Historically, Excel automation relied on VBA (Visual Basic for Applications). VBA does not natively understand JSON. Parsing JSON in VBA requires importing third-party libraries (like VBA-JSON) and utilizing clunky dictionary objects.

While Microsoft is slowly introducing "Office Scripts" (which use TypeScript) to Excel on the Web, the desktop ecosystem remains heavily anchored to Power Query for data ingestion.

Performance and Constraint Comparison

When deciding which platform to use for JSON integration, consider the hard technical limits:

Feature	Google Sheets	Microsoft Excel
Max Cell Limit	10 Million	17 Billion (Data Model)
JSON Parsing Engine	Javascript (V8)	Power Query (M-Code)
Create Web Endpoints	Yes (Apps Script)	No
Real-time API Fetching	Fast (Cloud execution)	Slow (Local execution)
Nested Array Handling	Requires custom scripts	Native visual expansion

Architectural Verdict

If your goal is to build a lightweight backend, fetch data from modern web APIs, or quickly convert tabular data into JSON for a web application, Google Sheets is vastly superior due to its Javascript foundation.

If you are dealing with massive payloads (over 50MB of JSON) or complex nested architectures that need to be flattened into relational data models for local business intelligence, Excel’s Power Query is unmatched.

(If you just need to convert a simple spreadsheet into a JSON array without writing code, use our local CSV/JSON Data Converter to bypass both platforms entirely).