What is Saiku used for?

Saiku is an open-source semantic layer and OLAP analytics tool built on Mondrian and Apache Calcite, serving Excel, dashboards and AI agents. It is a good fit for defining governed metrics once for all tools, analyzing cubes from Excel with pivot tables and giving AI agents safe access to business metrics.

Is Saiku open source?

Yes. Saiku is open source under the Apache-2.0 licence. Its source code is on GitHub at spiculedata/saiku and is written mainly in Java.

Yes. Saiku is open source, so the software itself is free to use.

Can I self-host Saiku?

Yes. Saiku can be self-hosted on your own server or infrastructure.

What is Saiku an alternative to?

Saiku is an open-source alternative to Tableau, Qlik, Sisense and Power BI. Other open-source alternatives to Tableau include Superset, Metabase and Lightdash.

Is Saiku actively maintained?

Yes. The most recent commit to Saiku was on 2 October 2026, and the latest release is v4.8.0, published on 15 September 2026. The project has 1.3k stars on GitHub.

Saiku: open-source alternative to Tableau, Qlik, Sisense

About Saiku

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.

Key features

Drag-and-drop OLAP browser
MDX and XMLA access from Excel
Mondrian with Apache Calcite SQL planner
MCP and typed REST API for AI agents
Docker image with demo mode
Support for modern lakehouse engines

Good fit for

→Defining governed metrics once for all tools
→Analyzing cubes from Excel with pivot tables
→Giving AI agents safe access to business metrics

Built with: Java
Tags: semantic-layer; olap; mondrian; mdx; business-intelligence; analytics; mcp; java; calcite

Saiku: questions and answers

What is Saiku used for?: Saiku is an open-source semantic layer and OLAP analytics tool built on Mondrian and Apache Calcite, serving Excel, dashboards and AI agents. It is a good fit for defining governed metrics once for all tools, analyzing cubes from Excel with pivot tables and giving AI agents safe access to business metrics.
Is Saiku open source?: Yes. Saiku is open source under the Apache-2.0 licence. Its source code is on GitHub at spiculedata/saiku and is written mainly in Java.
Is Saiku free?: Yes. Saiku is open source, so the software itself is free to use.
Can I self-host Saiku?: Yes. Saiku can be self-hosted on your own server or infrastructure.
What is Saiku an alternative to?: Saiku is an open-source alternative to Tableau, Qlik, Sisense and Power BI. Other open-source alternatives to Tableau include Superset, Metabase and Lightdash.
Is Saiku actively maintained?: Yes. The most recent commit to Saiku was on 2 October 2026, and the latest release is v4.8.0, published on 15 September 2026. The project has 1.3k stars on GitHub.