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AI · alternatives · 2026

24 alternatives to DataSloth - Query Pandas using natural language

Natural language Pandas queries and data generation powered by GPT-3 - ibestvina/datasloth

DataSloth is a tool that lets users query Pandas dataframes using natural language instead of writing code. It transforms plain English questions into Pandas operations, making data analysis accessible to those without… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. DataSloth - Query Pandas using natural language launched in 2022; newer entries below may have overtaken it.

  1. 1

    Hi HN community. We are excited to open source Dataherald’s natural-language-to-SQL engine today (https://github.com/Dataherald/dataherald). This engine allows you to set up an API from your structured database that can answer questions in plain English. GPT-4 class LLMs have gotten remarkably good at writing SQL. However, out-of-the-box LLMs and existing frameworks would not work with our own structured data at a necessary quality level. For example, given the question “what was the average rent in Los Angeles in May 2023?” a reasonable human would either assume the…

    2023 · github.com · its alternatives →

  2. 2

    Long story short: We (Dataherald) just open-sourced our entire codebase, including the core engine, the clients that interact with it and the backend application layer for authentication and RBAC. You can now use the full solution to build text-to-SQL into your product. The Problem: modern LLMs write syntactically correct SQL, but they struggle with real-world relational data. This is because real world data and schema is messy, natural language can often be ambiguous and LLMs are not trained on your specific dataset. Solution: The core NL-to-SQL engine in Dataherald is an LLM based agent…

    2024 · github.com · its alternatives →

  3. 3

    Embed NL-to-SQL into your product

    2024 · its alternatives →

  4. 4

    Lightspeed query generation for SQL and Pandas

    2023 · lifeontrack.co · its alternatives →

  5. 5
    Capalyze▲809

    ChatGPT for datavores: scrape → ask → visualize

    2025 · capalyze.ai · its alternatives →

  6. 6

    Automate your document workflows

    2024 · panda-etl.ai · its alternatives →

  7. 7

    Query OpenAI’s GPT-3 from directly inside your database

    2023 · mindshub.ai · its alternatives →

  8. 8AN
  9. 9

    Converse with your data in natural language

    2023 · ai2sql.io · its alternatives →

  10. 10

    Turn plain language into powerful database queries

    2025 · text2query.com · its alternatives →

  11. 11

    Would love thoughts! Here is the HF page: https://huggingface.co/chatdb/natural-sql-7b

    2024 · github.com · its alternatives →

  12. 12

    Explore GitHub live data in natural language

    2023 · ossinsight.io · its alternatives →

  13. 13

    Paste in my prompt to Claude Code with an embedded API key for accessing my public readonly SQL+vector database, and you have a state-of-the-art research tool over Hacker News, arXiv, LessWrong, and dozens of other high-quality public commons sites. Claude whips up the monster SQL queries that safely run on my machine, to answer your most nuanced questions. There's also an Alerts functionality, where you can just ask Claude to submit a SQL query as an alert, and you'll be emailed when the ultra nuanced criteria is met (and the output changes). Like I want to know when somebody posts about…

    Dec 2025 · exopriors.com · its alternatives →

  14. 14

    Fastest way: csv/xls to dashboard report, no ChatGPT upload

    2023 · datasquirrel.ai · its alternatives →

  15. 15DS

    I played around with GPT-3 to build this demo. Select a public BigQuery dataset and describe your query in natural English, then edit the generated SQL as needed and execute it. https://app.tabbydata.com/sql-assistant-demo

    2021 · its alternatives →

  16. 16

    open-source agentic AI data assistant for the next generation of AI + Data products. - eosphoros-ai/DB-GPT

    2023 · github.com · its alternatives →

  17. 17
    PandasAI▲106

    The conversational way for dealing with data

    2023 · github.com · its alternatives →

  18. 18

    Python dev to an NLP data scientist with practical projects

    2022 · its alternatives →

  19. 19

    Simon(sfarshid) and I spend a lot of time on GitHub. As data nerds we put together a quick tool to explore your repository’s data. How it works: - Data Loading: We use dlt to pull data (issues, PRs, commits, stars) from GitHub - Semantic Layer: Relta wraps the underlying dataset into a semantic layer so the LLM doesn’t hallucinate. - Text-to-SQL: A text-to-SQL agent transforms your plain-English question into a query using the semantic layer - Generative Charts: assistant-ui dynamically generates a chart based on the SQL query - Refinements: If the semantic layer can’t handle your question,…

    2024 · github.com · its alternatives →

  20. 20

    🔎 Search the information available on a webpage using natural language instead of an exact string match. - model-zoo/shift-ctrl-f

    2020 · github.com · its alternatives →

  21. 21PU
  22. 22

    Query programming languages using natural language!

    2020 · codesnippetsearch.net · its alternatives →

  23. 23NL
  24. 24

    Hi folks, My friend Sami and I recently built Vizly, a Mac application that allows anyone to query their databases using plain English. Vizly is built on Llama 2, llama.cpp, and runs fully on-prem (edit: meaning everything is local and your data never leaves your own computer). We are running two Llama models, one for natural language to SQL translation, and another that uses the results from the SQL to render visualizations. That means there are no external APIs and all the AI models are running locally on your MacBook. We tried to make Vizly very easy to share as well. Every Vizly instance…

    2023 · vizly.fyi · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →