XIAOJUSURVEY is an enterprises form builder and analytics platform that allows users to create questionnaires, exams, polls, quizzes, and analyze data online.
First read
didi/xiaoju-survey is active enough to inspect further, but the surrounding proof is thinner. Use the source repository and nearby comparisons to decide whether this is rising substance or just short-term visibility.
3.8K public stars in the current GitStar snapshot.
Needs a narrower context read
Last commit Jul 20, 2026.
Active enough
Treat stars as discovery context until a linked package appears.
No linked package mapping
One or more key signals are partial, so GitStar keeps the interpretation conservative.
Partial snapshot
Snapshot facts
Compare lens
pubkey/rxdb and firecrawl/firecrawl are the closest comparison targets GitStar found. A side-by-side comparison usually tells you more than a single raw rank.
Signal trail
Read the recent motion first. This block is for deciding whether the repository still looks alive, compounding, or flattening before you trust stars alone.
Package reality
No linked npm or PyPI package is mapped for this repository yet, so the page leans more heavily on GitHub-visible popularity and should be read more conservatively.
GitStar expects a package signal here, but no npm or PyPI package is linked to this repository yet.
Validation note
GitStar can summarize public signals for didi/xiaoju-survey, but the GitHub repository is still the primary place to confirm release cadence, issue activity, and maintainer intent.
GitStar surfaces public popularity and package signals. These rankings are not endorsements, security reviews, or investment advice.
Why this rank
This repository stands out because it combines fresh update.
Reconstructed from current stars and cached daily/weekly/monthly deltas.
GitStar can see repository momentum, but it does not have a reliable linked package signal yet.
Treat stars and recent movement as discovery context only until npm or PyPI usage is available.
Shares the data category footprint with didi/xiaoju-survey, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the data category footprint with didi/xiaoju-survey, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the data category footprint with didi/xiaoju-survey, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the data category footprint with didi/xiaoju-survey, so the comparison is closer to a same-problem decision than a same-language coincidence.
GitStar picked rxdb + firecrawl as the closest next comparison from the related repository set.
[](https://gitstar.space/repo/didi/xiaoju-survey)<a href="https://gitstar.space/repo/didi/xiaoju-survey"><img src="https://gitstar.space/api/badge/didi/xiaoju-survey" alt="GitStar"></a>The local-first database that runs on every JS runtime and replicates with your existing backend - no vendor, no lock-in - https://rxdb.info/
The context API to search, scrape, and interact with the web at scale. 🔥
Chat2DB is a free, cross-platform, local-first database client and SQL workspace for developers, DBAs, analysts, and data teams. Connect to 40+ databases, manage data, edit and run SQL, and use your own AI model to generate, explain, and optimize queries. Available on desktop, web, Docker, and CLI, with MCP support.
🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using Agentic Retrieval 🔄.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report
This page provides a quick overview of didi/xiaoju-survey based on GitStar's cached data. The signal chart reconstructs approximate checkpoints from current stars plus cached daily, weekly, and monthly star deltas, so it is best read as directional context rather than as a precise historical audit log.
Want to show your project's ranking? Copy the badge embed code above and add it to your README.