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Sqliteviz is a client-side, offline-first web application that lets you upload SQLite databases, CSV, JSON, or NDJSON files and query them with SQL to generate interactive charts, pivot tables, and graphs—all without sending data to a server. It runs entirely in your browser as a progressive web app (PWA) and can be installed as a desktop application.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | lana-k/sqliteviz |
| Owner | lana-k |
| Primary language | JavaScript |
| License | Apache-2.0 — OSI-approved |
| Stars | 2.4k |
| Forks | 135 |
| Open issues | 20 |
| Latest release | 0.30.0 (2026-04-15) |
| Last updated | 2026-07-05 |
| Source | https://github.com/lana-k/sqliteviz |
What sqliteviz is
Built on Vue.js with sql.js for in-browser SQLite execution, Plotly.js for charting, PivotTable.js for pivot operations, and Sigma.js/Graphology for graph visualization. Data processing is entirely client-side; the application is distributed as a single-page app (SPA) and supports CSV parsing via Papa Parse.
Get the sqliteviz source
Clone the repository and explore it locally.
git clone https://github.com/lana-k/sqliteviz.gitcd sqliteviz# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Data is processed entirely in the browser; verify sql.js performance limits match your typical dataset sizes before deployment.
- PWA installation requires HTTPS in production; plan for secure hosting and verify offline functionality across target browsers.
- User inquiries and workspaces are stored in browser localStorage; implement user guidance on data persistence and backup strategies.
- Memory consumption can spike during large CSV imports or complex queries; monitor browser memory usage in your user base.
- File format support is limited to SQLite, CSV, JSON, and NDJSON; confirm compatibility with your data pipeline outputs before adoption.
When to avoid it — and what to weigh
- Large-scale or production data warehouses — The in-browser SQLite engine (sql.js) is not designed for multi-gigabyte datasets or high-concurrency workloads. For enterprise data warehousing, use Redash, Tableau, or similar server-backed solutions.
- Shared team dashboarding with persistent state — Sqliteviz is single-user and browser-based; it lacks collaborative dashboarding, role-based access, or centralized query management needed for multi-user environments.
- Real-time streaming or live data updates — The application is designed for static file-based analysis. There is no built-in support for streaming data sources, scheduled queries, or automatic refresh mechanisms.
- Complex data orchestration or ETL pipelines — Sqliteviz is a visualization tool, not an ETL platform. If you need data transformation workflows, scheduling, or integration with external systems, use dedicated tools (Airflow, dbt, etc.).
License & commercial use
Licensed under Apache License 2.0, a permissive open-source license that permits commercial use, modification, and distribution with attribution and liability disclaimers.
Apache-2.0 permits commercial use and modification. However, verify compliance with your use case: if you modify the code for internal or commercial purposes, retain the license header and document changes. Consult legal counsel if bundling with proprietary software or if licensing obligations with dependencies apply.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Low |
| DEV.co fit | Good |
| Assessment confidence | High |
Sqliteviz processes all data client-side, eliminating server-side data breach risks. No network transmission of raw data occurs. Consider: (1) sql.js and dependency vulnerabilities—track security advisories; (2) browser sandbox limitations—data persists in localStorage; (3) supply-chain risk—verify integrity of npm dependencies (Plotly, Vue, Papa Parse, etc.) before use in sensitive environments. No built-in encryption; user data is stored unencrypted in browser storage.
Alternatives to consider
Redash
Server-backed open-source BI platform with multi-user dashboards, query scheduling, and database connectivity. Better for teams and persistent workspaces; requires infrastructure.
Metabase
Lightweight, self-hosted BI tool with native database connectors and permissive AGPL license. Simpler than Redash for small teams; still requires backend deployment.
DuckDB + Observable / Jupyter
DuckDB is a fast SQL engine for local analysis; pair it with Observable notebooks or Jupyter for interactive visualization. Better for developers; higher setup overhead.
Build on sqliteviz with DEV.co software developers
Review the live demo at sqliteviz.com/app, audit the Apache-2.0 licensed codebase on GitHub, and test with your typical dataset sizes. Contact us for deployment planning, security assessment, or integration with your data pipeline.
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sqliteviz FAQ
Can I use sqliteviz with my production PostgreSQL database?
Is my data secure when I upload it to sqliteviz.com/app?
Can multiple users collaborate on the same analysis?
What is the maximum dataset size I can work with?
From evaluation to production software
DEV.co pairs senior engineers with teams adopting tools like sqliteviz. Our software development services span open-source databases architecture, implementation, and the AI development services that increasingly sit alongside them.
Ready to evaluate sqliteviz for your data visualization needs?
Review the live demo at sqliteviz.com/app, audit the Apache-2.0 licensed codebase on GitHub, and test with your typical dataset sizes. Contact us for deployment planning, security assessment, or integration with your data pipeline.