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A collection of developer tools in one place in your browser

Microsoft Office Excel
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Airtable
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Apple Numbers
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100% local, zero uploads. Process millions of rows entirely in your browser. The ultimate privacy-first toolkit for CSV, ecommerce, and marketing data.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | devtoolsadvanced.com | dataprep.dev |
| Pricing | — | |
| Platforms | — | |
| Company | — | Startup from the United States · 1 - 9 employees · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of DevTools Advanced yet.
The Browser Data Toolkit for Privacy-Conscious Professionals dataprep.dev is a 100% local, pure-browser data processing engine designed to solve the biggest headaches in data preparation: Excel crashes and privacy risks. Powered by cutting-edge DuckDB-Wasm technology, our toolkit brings...
What each product offers, as listed by its team.


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An editorial look at what each product does well and who it suits.


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Recommended for
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Instant SQL on CSV in Browser (DuckDB-Wasm) - Zero Uploads
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing DevTools Advanced and dataprep.dev.
dataprep.dev's answer:
I was trying to clean up a massive, messy Shopify order export. Excel kept freezing, and I absolutely refused to upload sensitive customer emails to random online converters. I got so frustrated that I decided to stop complaining and build a local-first toolkit to solve my own workflow nightmare.
dataprep.dev's answer:
1, Indie hackers and solo founders. 2, Boutique digital marketing agencies. 3, Privacy-conscious data freelancers.
dataprep.dev's answer:
Most data tools force you to upload your CSVs to their servers. We don't. We compiled DuckDB into WebAssembly, meaning you get a blazing-fast, database-level engine running entirely inside your local browser tab. It's 100% private and works instantly.
dataprep.dev's answer:
If you try to open a 2GB CSV in Excel, it freezes and crashes. If you use Python Pandas, you have to write code and manage environments. dataprep.dev gives you the power of code (SQL queries, regex, merging 50 files) with a simple drag-and-drop UI, without ever freezing your computer.
dataprep.dev's answer:
E-commerce sellers flattening messy Shopify exports, performance marketers cleaning ad reports, and data analysts who need to anonymize PII (GDPR compliance) before feeding datasets to AI models like ChatGPT.
dataprep.dev's answer:
DuckDB-Wasm is the core data engine handling the heavy lifting. The frontend is built with React/Next.js and styled with Tailwind CSS. It's a modern, serverless architecture.
Share your experience with using DevTools Advanced and dataprep.dev. For example, how are they different and which one is better?
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