Open-source Logi Symphony alternatives

Apache Superset is a data exploration and visualization platform that runs as a web application. Analysts and business users can connect it to a database, build charts without code, assemble them into dashboards and share them, so it can augment or replace proprietary business intelligence tools for many teams.

The no-code chart builder sits next to a web-based SQL editor for advanced queries, and a lightweight semantic layer lets teams define reusable dimensions and metrics. Visualizations range from simple bar charts to geospatial views. Superset can query any SQL datastore or engine provided a matching Python database driver and SQLAlchemy dialect exist, including Presto, Trino and Athena. A configurable caching layer reduces database load, and security roles and authentication options are extensible.

The stack is Python with Flask on the back end and React on the front end, under the Apache-2.0 license. A REST API and extension framework allow programmatic control and customization. Documentation is split into guides for users, administrators and developers, and it is a typical choice for organizations that want a self-managed BI layer.

Metabase is an open-source business intelligence and embedded analytics tool meant for everyone in a company, not only analysts. People can ask questions about their data without knowing SQL, while an SQL editor is available for more complex queries. Written in Clojure, it connects to databases such as PostgreSQL and MySQL.

Its features include interactive dashboards with filters, auto-refresh and custom click behavior, plus documents for long-form analysis that colleagues can comment on. An AI assistant called Metabot helps answer questions and write queries, and you can build your own AI agent against your data. Data Studio supports transforming raw data into analytics-ready tables and defining canonical metrics. Alerts and scheduled dashboard subscriptions go to email, Slack or a webhook, and a Library plus Git integration help version your work.

Metabase can also be embedded in your own product with components for charts, dashboards, a data browser and AI chat, and granular permissions work for internal teams and embedded customers. You can self-host it or use Metabase Cloud, which the project says includes support, backups, upgrades and a free trial. The repository license is listed as 'Other', so review its terms.

Lightdash is an open-source business intelligence platform that it describes as agentic BI, meant for data teams that want analytics to be shipped like software. Metrics, joins, permissions, business logic and caching are defined once in a context layer, and that layer feeds MCP, SDKs, embedded analytics, data apps, AI agents and dashboards.

Analytics can be built as code: metrics, charts and dashboards live as files that you can edit with coding agents, preview from the Lightdash CLI, validate in CI and review in pull requests. Business users can pose questions in plain English, browse dashboards or build custom data apps, all while governance stays in place. Agents answer from the context layer rather than guessing from raw tables, respect permissions and return queries that can be inspected. The repository topics mention dbt.

Lightdash is written in TypeScript. The vendor recommends starting with Lightdash Cloud, which needs no infrastructure to run, and also offers a live demo, documentation and a sales call. The repository lists its licence as other, so check the terms before self-hosting.

Graphic Walker, from Kanaries, is an open-source visual analytics tool positioned as an alternative to Tableau. Users build charts and pivot tables by dragging fields onto visual channels, and can also ask questions in natural language. It is released under the Apache-2.0 license.

Its main distinction is that it ships as a React component that you embed in your own application, rather than as a heavy business-intelligence platform. The interface follows a grammar of graphics based on Vega-Lite, supports spatial visualizations from GeoJSON and TopoJSON, and includes light and dark themes. A data explainer suggests why patterns occur, and a hand-writable chart specification called TerseSpec describes charts in compact form.

Computation can run in the browser using web workers, which allows a purely front-end setup, or queries can be passed to your own computation service, for example one using DuckDB as in the Python companion PyGWalker. It suits developers who want to add exploratory analysis to a product and data scientists who want fast visual exploration without a full BI stack.

Shaper is an open-source tool for building data dashboards, reports and customer-facing analytics by writing SQL. It is developed by Taleshape and powered by DuckDB, and it aims to make analytics simple for developers: you write queries, and Shaper turns them into charts and shareable pages.

The data visualization side is SQL-first and designed to work with AI, with a Git-based workflow and the ability to query across data sources. Embedded analytics features include white-labeling and custom styles, row-level security through JWT tokens, and embedding via JavaScript and React SDKs without an iframe. Automated reporting can generate PDF, PNG, CSV and Excel files, send scheduled alerts and reports, and share password-protected links.

Shaper is written in Go and licensed under MPL-2.0. You can try it with a single Docker command or follow the deployment guide for production. Taleshape also offers managed hosting, in its own cloud or in your infrastructure, plus hands-on support, and explains the shared-responsibility model between self-hosting and managed service. It suits product teams adding analytics to their apps.