Open-source Amazon QuickSight 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.

Redash is an open-source business intelligence and data exploration tool that works entirely in the browser. SQL users connect it to a data source, write queries, turn results into visualizations and share them, so that colleagues without SQL skills can use the results too.

The query editor accepts both SQL and NoSQL queries and offers a schema browser plus auto-complete. Visualizations are built by drag and drop and can be combined into dashboards, and every chart or query has a shareable URL that supports collaboration and peer review. Charts and dashboards can refresh on a schedule, and alerts can notify you when results cross a threshold. Topics mention many sources, including Redshift, BigQuery, Athena, MySQL, PostgreSQL and Databricks.

Redash is written in Python and JavaScript and licensed under BSD-2-Clause. You deploy it on your own infrastructure, commonly with Docker, and it is aimed at analysts and engineers who want a lightweight, query-first dashboard tool rather than a heavy BI suite.

DataEase is an open-source BI tool that helps users analyze data and spot business trends. It connects to a wide range of data sources, lets you build charts by dragging and dropping, and supports sharing results with others. The project describes itself as an open-source alternative to Tableau and is developed by FIT2CLOUD in Java, with a Chinese-language README.

Supported data sources include OLTP databases such as MySQL, Oracle, SQL Server, PostgreSQL, MariaDB, Db2, TiDB and MongoDB, OLAP engines such as ClickHouse, Apache Doris, Apache Impala and StarRocks, Amazon Redshift, Excel and CSV files, and API sources. The stack uses Vue.js, Spring Boot, AntV for charts, Apache Calcite and SeaTunnel, and Docker. Installation uses an offline package on a Linux server with at least 2 cores and 4 GB of memory, or the 1Panel app store. V3 uses the FIT2CLOUD Open Source License, essentially GPLv3 with extra restrictions, and commercial licensing is available.

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.