Alternatives
Products that do what Dataptic — Visual Data Pipeline Builder does
Data analytics,manipulation and science without writing code
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Every data pipeline job I had to tackle required quite a few components to set up: - One tool to ingest data - Another one to transform it - If you wanted to run Python, set up an orchestrator - If you need to check the data, a data quality tool Let alone this being hard to set up and taking time, it is also pretty high-maintenance. I had to do a lot of infra work, and while this being billable hours for me I didn’t enjoy the work at all. For some parts of it, there were nice solutions like dbt, but in the end for an end-to-end workflow, it didn’t work. That’s why I decided to build an…
2024 · github.com
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Hi HN! I’m Alex from Parabola (https://parabola.io). Parabola is a visual programming tool for creating functional data flows that everyone can use. It’s entirely drag-and-drop, handles data sizes much larger than a traditional spreadsheet, calculates everything live, and can run your flows on a schedule of your choosing. I used to work in strategy consulting, doing data analytics for SMBs and Fortune 500 companies. The amount of time wasted on menial tasks was astounding. Things like cleaning data, generating custom reports, creating human workflows to solve shortcomings in third…
2018 · parabola.io
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2022 · github.com
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2021 · datablocks.pro
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Hey HN, I am Alex. I am open sourcing Data Studio, a lightweight data exploration IDE in your browser that runs locally. Try it: https://local.dataspren.com (no account needed, runs locally) More information: https://github.com/dataspren-analytics/data-studio I love working with data (Postgres, SQL, DuckDB, DBT, Iceberg, ...). I always wanted a data exploration tool that runs in my browser and just works. Without any infra or privacy concerns (DuckDB UI came quite close). Features: - Data Notebooks - SQL cells work like DBT models (they materialize to views) -…
Feb 2026 · github.com
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2022 · github.com
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I built CSV GB+ by Data.olllo, a local data tool that lets you open, clean, and export gigabyte-sized CSVs (even billions of rows) without writing code. Most spreadsheet apps choke on big files. Coding in pandas or Polars works—but not everyone wants to write scripts just to filter or merge CSVs. CSV GB+ gives you a fast, point-and-click interface built on dual backends (memory-optimized or disk-backed) so you can process huge datasets offline. Key Features: Handles massive CSVs with ease — merge, split, dedup, filter, batch export Smart engine switch: disk-based "V Core" or RAM-based "P…
2025 · apps.microsoft.com
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Hello HN. I've always found writing data visualisation scripts boring and repetitive in data science workflows earlier in my career, so I built this tool to automate it. The available methods are based on my experience in econometrics where histograms and scatterplots were the starting points to check data distributions. The link is to the documentation and the app is freely available at https://visprex.com, and if you're curious about the implementation it's open source at https://github.com/visprex/visprex. I'd appreciate any comments and feedback!
2024 · docs.visprex.com
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Hey HN! We’ve built Pretzel, an open-source data exploration and visualization tool that runs fully in the browser and can handle large files (200 MB CSV on my 8gb MacBook air is snappy). It’s also reactive - so if, for example, you change a filter, all the data transform blocks after it re-evaluate automatically. You can try it here: https://pretzelai.github.io/ (static hosted webpage) or see a demo video here: https://www.youtube.com/watch?v=73wNEun_L7w You can play with the demo CSV that’s pre-loaded (GitHub data of text-editor adjacent projects) or upload…
2024 · github.com
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Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020
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