DataLine

What it does

DataLine is an AI data analysis and visualization tool for technical and non-technical people who want to explore data, and for developers drafting SQL or exploring databases. Users connect a database or provide supported files, ask questions in natural language, and can generate and execute SQL, create or adjust charts, and edit, save, and rerun query results. Outputs include tables, charts, and reports; the website also describes dashboards.

The project is open source and is run locally through an executable or Docker, with a browser interface served at localhost; the repository also documents a manually configured backend and frontend. Supported sources listed in the repository include PostgreSQL, MySQL, Snowflake, Azure SQL Server, Microsoft SQL Server, SQLite, CSV, Excel, and sas 7 bdat, while the website lists a shorter set. The repository says data is stored on the device and hidden from LLMs by default, with an option to disable that behavior. It also notes that authentication is unavailable in the executable and that Excel imports require a particular sheet structure. The repository is currently seeking maintainers, so check compatibility and maintenance before depending on it.

What it can do

• Ask questions about data in natural language
• Generate and execute SQL
• Connect to databases and data files
• Create and modify charts from natural language
• Edit, save, and rerun SQL results
• Generate tables, charts, reports, and dashboards

Works with

• PostgreSQL
• MySQL
• Snowflake
• Azure SQL Server
• Microsoft SQL Server
• SQLite
• CSV
• Excel
• sas 7 bdat

Before you choose

• The website and repository list different subsets of supported sources; verify support for a specific connector before relying on it.
• The repository says basic authentication is supported in self-hosted mode but not in the executable; its documented setup supports a single user.
• Excel imports have structural requirements, including a header row and removal of padding rows or columns; incorrectly detected headers can cause import problems.
• The repository is seeking maintainers. Confirm release compatibility and support before deploying it for ongoing work.
• Configure the required model-provider credentials; provider charges may apply. Review data-sharing settings before connecting sensitive data.

Listed under

• Data
• Analytics and BI
• Dashboards
• Data analysis
• Data visualization
• Developers
• Non-technical users
• Open source

Get started

Download an executable, install through Homebrew, or run the official Docker image.

1. Choose an installation option: executable, Homebrew, or Docker, following the repository instructions for your system.
2. Start DataLine and open its browser interface at localhost:7377.
3. Connect a supported database or import a supported file, then ask a question or request a chart.

The repository is open source. Configured model-provider usage and operating infrastructure may carry separate charges; no managed-service price is verified.

We couldn’t find published prices for DataLine. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 1 Nov 2026. Each source supports part of the overview; availability and prices can change.

• DataLine - Chat with your Data ↗dataline.app
• GitHub - RamiAwar/dataline: Chat with your data - AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake, SQLite... · GitHub ↗github.com
• DataLine - Chat with your Data ↗dataline.app
• DataLine - Chat with your Data ↗dataline.app
• DataLine - Chat with your Data ↗dataline.app

Company website

dataline.app: product, pricing and policy pages

YC directory mirror

Batch and company name

Human review

Checked by a person

knowledge_base

manual_review

Last checked 1 Nov 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.