Open-source IBM Cognos Analytics 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.

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.

Saiku began in 2010 as an open-source OLAP browser for Mondrian and was rebuilt in 2026 as a modern semantic layer for analytics. It defines business cubes once and then exposes them to different consumers: a drag-and-drop browser interface, Excel through MDX and XMLA, dashboards, and AI agents through MCP.

In the browser, users drag fields onto rows, columns and filters and the application writes MDX for them. The back end uses a fork of Mondrian 4.8 with an Apache Calcite-based SQL planner, which can reach modern engines such as lakehouse systems. A typed REST interface allows AI agents to query data without handling MDX. A demo mode ships with a self-contained H2 database and the FoodMart sample cube.

Saiku is written in Java and licensed under Apache-2.0. It runs from a Docker image, which runs as a non-root user and requires setting an admin password for real deployments, and a hosted demo instance resets nightly. It suits analytics and BI teams that need governed, reusable metric definitions across spreadsheets, dashboards and AI tools.

DataLens is a modern business intelligence and data visualization system. It was developed and used extensively as a primary BI tool inside Yandex and is also offered as part of the Yandex Cloud platform, while the open-source version can be run independently.

Topics describe it as an analytics, dashboard, reporting and SQL visualization tool. The quick start needs Docker and the Docker Compose plugin; cloning the repository and running a start command launches all containers, and the UI is then available on port 8080, which can be changed with an environment variable. For production use the maintainers recommend generating a compose file with random secrets, which stores a generated admin password in the environment file.

Charts can use D3.js, or the proprietary Highcharts library if you enable it, in which case you must comply with Highcharts' own license. DataLens is licensed under Apache-2.0, has a roadmap, release notes and a Telegram community, and suits teams that want self-hosted dashboards.

Datart is a data visualization platform built by the original creators of the Davinci BI project, aimed at enterprises that need to build reports, dashboards, large-screen displays and visual data applications. It positions itself as more open, adaptable and intelligent than typical closed business intelligence products, where users are limited to built-in data sources and chart types.

The platform's design centers on three principles: openness, achieved through standardized processes for managed visualization apps, standardized interactions such as filtering, drilling and linking between charts, and pluggable extension points at the data source, chart and visualization layers; integrability, so Datart can be embedded into other systems using its login, permissions and SDK integration points rather than only used as a standalone platform; and augmented analytics, aiming to go beyond showing what happened in the data toward explaining why, through extensible analytical capabilities.

Datart is written in TypeScript and React and uses chart libraries including ECharts and D3. It is released under the Apache-2.0 license, with a public demo, deployment and quick-start guides, and an active community supported through issue tracking and a WeChat discussion group.