Text-to-SQL / NL2SQL / conversational BI (ChatBI)
SQLBot is a stand-alone conversational BI server that uses LLMs and RAG to turn natural-language questions into SQL against user databases and shows answers as charts/insights.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
GPL-licensed Python ChatBI with recent activity and the same chat-over-BI workflow; choose when a Python/GPL deployment is preferable to the DataEase Docker stack.
ChatBI is a BI system interacted by chat with LLM
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Embeddable agentic text-to-SQL SDK with no RAG/semantic layer; choose when building a custom stack and you want self-correcting SQL generation plus tracing.
Agentic text-to-SQL SDK: hand the LLM one execute_sql tool and let it explore the schema, test queries, and self-correct — no RAG, no semantic layer. 20/20 on an 80-table Spider run. Built-in tracing and scenario support.
Java data-asking system built on pre-modeled semantics; choose when you need a controlled vocabulary/data model instead of RAG-based schema discovery.
Asking yours data in a natural language way through pre-modeling (data models and semantic models).
Python text-to-SQL library that uses retrieval generation; choose when you need an embeddable engine rather than a full ChatBI server.
🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using Agentic Retrieval 🔄.
Conversational data-analysis library for SQL/CSV/parquet via Python; choose when you need an embeddable pandas-style API rather than SQLBot's server/UI.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Old Java NL2SQL/BI demo system with no updates in ~3 years; choose if you are Java-bound and can accept a stale dependency.
基于大模型LLMs的智能文本SQL生成能力，结合数据可视化，实现下一代对话式系统自动生成图表展示和dashboard、数据分析的BI系统。
AWS Bedrock/OpenSearch reference stack for RAG-based BI; choose if you are AWS-native and want a deployable sample rather than a maintained product.
A solution guidance for Generative BI using Amazon Bedrock, Amazon OpenSearch with RAG
E-commerce-specific full-stack NL2SQL learning app; choose if you want a small reference implementation for that scenario, not a general ChatBI platform.
📊 电商数仓智能问数 AI Agent，最适合用于系统学习 LangGraph 的实战项目：基于 LangGraph、FastAPI、Qdrant、Elasticsearch、MySQL 与 React，完整实现元数据知识库、混合检索、自然语言生成 NL2SQL 生成校验、SQL 执行与流式查询展示。前后端完整代码全栈可跑，Docker 环境一键部署，配套 ai-agents-from-zero 免费教程与章节代码分支。适合系统学习大模型应用、数据分析 Agent 和企业级 AI 工程落地。
Broader AGPL data-intelligence agent from ~2 years ago; choose if you need document/image plus database questions and can accept no recent maintenance.
One-stop data intelligence agent, providing insights from all mainstream data formats in a single dialogue box, including documents, databases, business systems, and images.一站式数据智能体，一个对话框提供所有主流格式数据的见解，包括文档、数据库、业务系统和图像。
These projects were analysed and named SQLBot among their alternatives. The relationship is not symmetric — how SQLBot rates them is a separate judgement, made when SQLBot is analysed in its own right.
calls SQLBot “choose when you only need a RAG-based text-to-SQL engine to embed in your own system.”
一款真正的 AI 报表诞生了！JimuChatBI —— 首款免费开源对话式智能数据分析产品（Chat2BI）。 一句话生成报表和数据大屏，支持对话式 AI 修改优化；类 Excel 在线报表设计，兼容国产信创数据源。 对着 AI 说句话，报表就出来了——表格、图表、分组汇总自动生成，复杂报表场景轻松应对。想做数据大屏？同样一句话搞定，让数据分析进入 AI 时代。