Ross ROSS = Recommend OSS · open-source software intelligence for agents

RamiAwar/dataline

Chat with your data - AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake, SQLite... observed · 2026-08-28

github.com/RamiAwar/dataline · homepage · TypeScript · GPL-3.0 (copyleft) observed · 2026-08-28

Health v2 · maintenance only

58/100

  • Activity 67
  • Release rhythm 28
  • Longevity 88
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 36
  • age_days: 1237
  • days_rel: 461
  • days_push: 203
  • n_releases_24m: 6

Full methodology

Adoption not part of the score

1594 stars · 164 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DataLine is an open-source, privacy-focused AI data analysis and visualization application that lets users chat with their data in natural language. It connects to CSV files and databases like Postgres, MySQL, Snowflake, SQLite, and SQL Server to generate charts, tables, and reports locally without sending raw data to the cloud.

Use cases

  • chat with my csv files using natural language
  • generate charts from a postgres database with ai
  • text2sql tool for non-technical users
  • self-hosted ai data analysis tool
  • visualize mysql data without writing sql
  • build reports and dashboards from sqlite
  • query snowflake data with an llm locally
  • explore a new database quickly with natural language

When to choose

  • you want natural-language querying of SQL databases or CSVs without writing SQL
  • data privacy matters and you want everything stored locally with data hidden from LLMs
  • non-technical team members need to explore data and export charts or reports
  • you want a self-hosted, open-source alternative to cloud BI chat tools

When to avoid

  • you need a full-featured traditional BI suite with pixel-perfect dashboards
  • you require guaranteed SQL correctness for production-critical queries since LLM output can be wrong
  • you need a managed cloud service with no local installation
  • your data sources are outside its supported connectors (e.g., NoSQL databases)

Facets

application · maturity active

data-visualization chatbot llm-inference rag search-engine database data-visualization data-science analytics databases artificial-intelligence self-hosted windows self-hosted cross-platform text2sql chat-with-data ai-data-analysis privacy-focused charts sql csv postgres mysql snowflake sqlite dashboards macos linux docker

4 sources

Member repositories

RepositoryRoleHealth v2
RamiAwar/datalinemain58

For agents

markdown · JSON · MCP: product_card(name="RamiAwar/dataline")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem