Quilt

A data mesh platform that enables teams to manage large datasets like code packages, providing centralized data cataloging, automatic versioning, and collaborative data workflows. Designed for machine learning, biotech, and analytics teams requiring robust data lineage and reproducibility.

Use it when

• •Version control for large datasets that exceed Git's capabilities
• •Managing ML training data with automatic lineage tracking and rollback capabilities
• •Collaborative data science projects requiring centralized data package management
• •Data governance initiatives needing audit trails and access control
• •ML model versioning alongside corresponding training datasets
• •Scientific research requiring reproducible data workflows and provenance
• •Cross-team data sharing with standardized packaging and metadata
• •AWS-native data management workflows requiring S3 integration

Watch out

• ⚠Primarily designed for AWS ecosystem, limited support for other cloud providers
• ⚠Learning curve for teams unfamiliar with package management concepts
• ⚠Storage costs can accumulate quickly with large datasets and multiple versions
• ⚠Requires additional infrastructure setup beyond basic Git workflows
• ⚠Limited community compared to established version control systems
• ⚠Documentation gaps for advanced use cases and enterprise deployments
• ⚠Performance overhead for small datasets where Git LFS might suffice
• ⚠Dependency on specific Python SDK for programmatic access

Available in stages

Installation

Example stacks