# spiculedata/saiku

Open-source semantic layer: one cube for Excel (MDX/XMLA), dashboards, and AI agents (MCP). Mondrian + Apache Calcite.

Repository: https://github.com/spiculedata/saiku
Canonical: https://ross.abutalabs.com/products/saiku
Homepage: https://saiku.bi
Language: Java
License: Apache-2.0
License Family: permissive
Topics: analytics, apache-calcite, business-intelligence, mcp, mdx, mondrian, olap, semantic-layer, xmla
Last push: 2026-08-25T23:46:25+00:00

## Health v2 (maintenance only)
Score: 98/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 95, longevity 100
- inputs: {"age_days": 5446, "days_push": 8, "days_rel": 32, "gap_med": 1.0, "n_releases_24m": 25}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1316, forks 655 (observed 2026-08-28T04:04:20.893179+00:00)

## What it is
Saiku is an open-source semantic layer and OLAP analytics server built on Mondrian and Apache Calcite, exposing one cube to Excel (MDX/XMLA), browser dashboards, and AI agents via a typed REST API and MCP. It is deployed as a Java web application with a Docker image and a drag-and-drop web UI.

## Use cases
- query olap cubes from excel via mdx and xmla
- build drag-and-drop bi dashboards in the browser
- let ai agents query a semantic layer without writing mdx
- run sql analytics over a lakehouse with trino and iceberg
- self-host an open-source business intelligence server
- expose a single semantic model to multiple bi tools

## When to choose
- you need a self-hosted open-source semantic layer serving Excel, dashboards, and AI agents from one cube
- your team already uses Mondrian/MDX and wants a modern Calcite-based backend
- you want MCP support so LLM agents can query analytics safely

## When to avoid
- you only need lightweight SQL dashboards without OLAP modeling
- you prefer a fully managed commercial BI suite
- your stack is not Java/JVM-friendly and you cannot run Docker

## Facets
- artifact type: application
- maturity: active
- function: analytics, search-engine, api-framework, mcp, data-visualization, chat-interface
- domain: analytics, databases, data-visualization, large-language-models, self-hosted
- platform: jvm, self-hosted, browser, cross-platform
- tags: semantic-layer, olap, mdx, xmla, mondrian, apache-calcite, business-intelligence, cubes, excel, dashboards, ai-agents, docker, web-server

## Member repositories
- spiculedata/saiku (main) score 98

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:20.893179+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:48:30.993288+00:00, confidence not recorded.
  - readme: https://github.com/spiculedata/saiku (fetched 2026-08-28T04:04:20.893179+00:00, sha 06c3c4a1ee48)
  - homepage: https://saiku.bi (fetched 2026-08-29T12:06:59.384198+00:00, sha 44136fa355b3)
- Data as of 2026-08-30T08:39:29.467469+00:00.