We built DataKit because data teams were drowning in tool sprawl—juggling between Excel, SQL clients, Jupyter notebooks, BI tools, and countless browser tabs just to analyze a single dataset. That constant context-switching killed productivity and made data work feel like a chore.
With DataKit, we're bringing the data analysis pipeline into your browser. Unlike traditional tools that require complex setups or force you to upload sensitive data to the cloud, DataKit runs entirely locally. You can query gigabytes of data, create visualizations, and run Python notebooks—all without your data ever leaving your machine.
What's live today:
• Process multi-GB files locally
• Run Python notebooks with pandas, numpy, and ML libraries pre-loaded
• Write SQL queries running entirely in your browser
• Ask questions in plain English and get SQL generated automatically without giving any single row of your data to any model
What's coming next:
• Collaborative workspaces
• Custom data transformation pipelines
• ML model integration
DataKit is all about giving data professionals a modern, privacy-first alternative that eliminates server uploads, reduces tool fatigue, and keeps your sensitive data exactly where it should be—on your machine.
@rohan_kadam3 Thanks Rohan! I will check it out soon!! Thanks for your support again
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Most platforms force you into one setup, so the “your data, your way” approach stands out. Curious to see how smooth the switch between local and cloud actually feels.
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This looks fantastic—love the privacy-first approach and the fact that everything runs locally. The all-in-one setup with SQL, notebooks, and visualization in the browser could really cut down on context switching. Excited to see how the collaborative features and custom pipelines evolve. 🚀
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Superb! I've been following the progress since the early days, and I love how thoughtfully this product was built from the ground up. It's powerful, it's beautiful, and it gives a sleek solution to a big challenge — privacy! Keep it up 🔥
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Congrats on launching, wish you the best
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As a developer, I used Datakit to get specific and anomalies in my back-end logs after a heavy load and stress test. I loved that I didnt have to "upload" my data to any thirdparty to be able to get those insights and could run very specific queries easily on a large amount of data.
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run sql and do data analysis for files you have locally. it’s such a cool product and i wish it existed when i was a data analyst / data engineer
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The "no server upload" promise is compelling - how do you handle datasets larger than browser memory limits?
Replies
Datakit
We built DataKit because data teams were drowning in tool sprawl—juggling between Excel, SQL clients, Jupyter notebooks, BI tools, and countless browser tabs just to analyze a single dataset. That constant context-switching killed productivity and made data work feel like a chore.
With DataKit, we're bringing the data analysis pipeline into your browser. Unlike traditional tools that require complex setups or force you to upload sensitive data to the cloud, DataKit runs entirely locally. You can query gigabytes of data, create visualizations, and run Python notebooks—all without your data ever leaving your machine.
What's live today:
• Process multi-GB files locally
• Run Python notebooks with pandas, numpy, and ML libraries pre-loaded
• Write SQL queries running entirely in your browser
• Ask questions in plain English and get SQL generated automatically without giving any single row of your data to any model
What's coming next:
• Collaborative workspaces
• Custom data transformation pipelines
• ML model integration
DataKit is all about giving data professionals a modern, privacy-first alternative that eliminates server uploads, reduces tool fatigue, and keeps your sensitive data exactly where it should be—on your machine.
Try it now:
https://datakit.page
We're eager for feedback—let us know what features would make your data workflow even
smoother!
Huge congrats on the launch, Datakit
Datakit
@rajpurohit_vijesh Thanks Rajpurohit!
Congrats on launching, wishing you all the best. If you have a chance, I’d love for you to check out my product as well. Appreciate any feedback!
Datakit
@rohan_kadam3 Thanks Rohan! I will check it out soon!! Thanks for your support again
Most platforms force you into one setup, so the “your data, your way” approach stands out. Curious to see how smooth the switch between local and cloud actually feels.
This looks fantastic—love the privacy-first approach and the fact that everything runs locally. The all-in-one setup with SQL, notebooks, and visualization in the browser could really cut down on context switching. Excited to see how the collaborative features and custom pipelines evolve. 🚀
Superb! I've been following the progress since the early days, and I love how thoughtfully this product was built from the ground up. It's powerful, it's beautiful, and it gives a sleek solution to a big challenge — privacy! Keep it up 🔥
Congrats on launching, wish you the best
As a developer, I used Datakit to get specific and anomalies in my back-end logs after a heavy load and stress test. I loved that I didnt have to "upload" my data to any thirdparty to be able to get those insights and could run very specific queries easily on a large amount of data.
The "no server upload" promise is compelling - how do you handle datasets larger than browser memory limits?