# VertaAI/modeldb

Open Source ML Model Versioning, Metadata, and Experiment Management

Repository: https://github.com/VertaAI/modeldb
Canonical: https://ross.abutalabs.com/products/modeldb
Language: Java
License: Apache-2.0
License Family: permissive
Topics: machine-learning, model-management, modeldb, mit, verta, model-versioning
Last push: 2024-07-23T17:06:34+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3606, "days_push": 771, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1749, forks 289 (observed 2026-08-28T04:05:30.988379+00:00)

## What it is
ModelDB is an open-source system for machine learning model versioning, metadata tracking, and experiment management. It versions models along with their code, data, config, and environment, and provides clients in Python plus a web frontend deployable via Docker or Kubernetes.

## Use cases
- track machine learning experiments and compare metrics
- version ML models with their code, data, and environment
- make ML models reproducible
- build performance dashboards and share experiment reports
- manage a model registry across development and deployment
- self-host an experiment tracking server for a data science team

## When to choose
- you need a self-hosted, open-source experiment tracking and model versioning backend
- your team works in Python and wants a client library for ML metadata
- you deploy on Docker or Kubernetes and want lifecycle tracking from development to monitoring

## When to avoid
- you only need lightweight local experiment logging without a server
- you want a fully managed MLOps SaaS with active vendor support
- you need a project with frequent recent releases and active development

## Facets
- artifact type: service
- maturity: maintenance
- function: machine-learning, monitoring, database, api-framework, developer-tools
- domain: machine-learning, data-science, self-hosted
- platform: python, self-hosted
- tags: mlops, experiment-tracking, model-versioning, model-registry, metadata-management, devops, docker, kubernetes, web-server

## Member repositories
- VertaAI/modeldb (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:30.988379+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 2026-08-30T03:28:46.375812+00:00, confidence not recorded.
  - readme: https://github.com/VertaAI/modeldb (fetched 2026-08-28T04:05:30.988379+00:00, sha 187218a4c52b)
- Data as of 2026-08-30T08:39:29.467469+00:00.