lakeFS

Git extension for versioning data, models, and ML experiments.

DVC (Data Version Control) brings software-engineering practices to machine learning: it versions datasets, models, and pipelines alongside code in any Git repository, storing large files in your own remote storage while keeping lightweight pointers in Git. Enables reproducible experiments, data/model lineage, and pipeline orchestration from the command line.

Multimodal database for AI — vectors plus raw data, versioned.

Deep Lake, by Activeloop, is a database for AI that stores vectors alongside raw multimodal data — text, image, video, audio, and metadata — in a single version-controlled format. It supports cross-modal queries and can stream data straight into training, and its open-source core can be self-hosted or run as a managed service. The newer Deep Lake PG unifies a serverless Postgres with its vector and tensor engine.

Open-source platform for the ML and GenAI lifecycle.

MLflow is an open-source platform for managing the full machine-learning and GenAI lifecycle — experiment tracking, model registry, deployment, and, more recently, LLM/agent observability. Its GenAI stack adds OpenTelemetry-based tracing, systematic evaluation with built-in metrics and LLM judges, and prompt versioning. Framework- and provider-agnostic, it runs on your own infrastructure with no vendor lock-in.