# Apache MADlib

**Canonical:** https://apis.io/providers/apache-madlib/  
**Website:** https://madlib.apache.org/  
**APIs profiled:** 1

Apache MADlib is an open-source library for scalable in-database analytics. It provides data-parallel implementations of mathematical, statistical, and machine learning methods for structured and unstructured data, executed within PostgreSQL or Greenplum Database. MADlib enables data scientists to run machine learning algorithms directly in the database using SQL.

## Kin Score — 14.5 / 100 (emerging)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 14.5).

| Facet | Score |
|---|---|
| Discoverability | 59.3 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 10.5 |
| Developer Ergonomics | 9.5 |
| Commercial Clarity | 26.3 |
| Access Clarity | 26.3 |

## Agent readiness — 3.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | documented |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Freemium — onboarding: unknown, pricing: freemium, trial: no (confidence: medium).

## APIs (1)

- **Apache MADlib** — MADlib provides SQL-callable functions for classification, regression, clustering, dimensionality reduction, graph analytics, time series analysis, deep learning with Keras/Tens...

## Security (2)

- **Apache Madlib Domain Security** — TLSv1.3 · HSTS · DMARC
- **Apache Madlib Vulnerability Disclosure** — security.txt · contact published

## Plans (1)

- **Apache Madlib Plans Pricing**

## Use cases (5)

- **Predictive Analytics** — Build predictive models for churn prediction, fraud detection, and demand forecasting directly on database data.
- **Recommendation Systems** — Implement collaborative filtering and content-based recommendation algorithms using in-database machine learning.
- **Customer Segmentation** — Cluster customers using K-Means and other algorithms to identify segments for targeted marketing.
- **Anomaly Detection** — Detect anomalies in time series and transactional data using statistical models running in-database.
- **Network Analysis** — Analyze social networks, supply chains, and communication graphs using built-in graph algorithms.

## Tags

In-Database Analytics, Machine-Learning, PostgreSQL, SQL, Statistics, Deep Learning

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/apache-madlib/). Scores are computed from the provider's own public artifacts under a published rubric.