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Dataline

Dataline is an open-source, TypeScript data-analysis application that accepts natural-language questions, generates and executes SQL, and produces visualizations and report-ready results from files and database connections.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Dataline — OpenViST project profile in AI Data & Analytics.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Dataline for exploratory analysis when you want to move from a question about a supported data source to a query and visual output in one application.

Who it is for

  • People who want to explore data without writing every query manually.
  • Backend developers who want help drafting SQL or exploring unfamiliar databases.

Documented uses

  • Ask natural-language questions about CSV or database data and generate SQL.
  • Modify and rerun queries while exploring results.
  • Create or refresh charts using natural-language requests.
  • Copy or export analysis results as charts, tables and reports.
Before you choose

Requirements & limits

The README documents binary or Homebrew installation options for desktop systems and an official Docker image. It gives localhost:7377 as the browser address. The repository declares a GPL-3.0 license.

  • The documented data sources include CSV, Excel, SQLite, PostgreSQL, MySQL, Snowflake, Azure SQL Server, Microsoft SQL Server and sas7bdat.
  • The project describes local storage and says data is hidden from default LLMs, with an option to disable that behavior.
  • The Docker setup uses a persistent volume and is described as supporting authentication and other features.
  • Dashboards and triggers appear as roadmap items, not listed supported features.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install and open Dataline on macOS with Homebrew

Install Dataline using the documented Homebrew commands and open its local interface.

Before you start

  • macOS
  • Homebrew

Steps

  1. Run brew tap ramiawar/dataline.

  2. Run brew install dataline.

  3. Run dataline.

  4. Open http://localhost:7377 in a browser.

Expected outcome

The local Dataline interface is accessible in a browser at localhost on port 7377.

Guide limitations

  • This guide covers installation and opening the interface, not connecting a data source or running an analysis.
Documentation 1 ↗
Source-based practical guide

Start Dataline with Docker

Run the documented Docker image with a persistent volume and open its local interface.

Before you start

  • Docker

Steps

  1. Run the command below.

    Documented command
    docker run -p 7377:7377 -v dataline:/home/.dataline --name dataline ramiawar/dataline:latest

  2. Open http://localhost:7377 in a browser.

Expected outcome

The Dataline frontend is available locally, with the named Docker volume mounted for persistence.

Guide limitations

  • The documented steps do not configure authentication or other Docker options.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
11 October 2026
Original website title
RamiAwar/dataline · Official homepage title · retained in its source language
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