{"categories":[{"label":"Database","url":"https://skillfed.io/packages/category/database/4"}],"enrichment":{"capability":"LaminDB is a data management system for organizing, querying, and governing multimodal datasets across diverse storage formats with built-in lineage tracking, versioning, and ACID compliance.","skillfed_tags":["data-lineage","scientific-data","biodata"],"use_cases":["Organize and query large collections of biological datasets (gene expression, spatial data, biosamples) with schema-based metadata and ontology support.","Track data lineage and code provenance across multi-step analysis pipelines to ensure reproducibility and audit trails.","Manage collaborative research projects with versioned datasets, branching for parallel experiments, and federated access across storage locations.","Integrate AI agent sessions with automatic logging of inputs, outputs, source code, and compute environments for reproducible agent-driven research.","Govern changes to datasets and models using git-like branching and versioning for regulated or high-stakes biotech workflows."],"what_it_does":"LaminDB is an open-source data management platform designed to handle multimodal scientific datasets across heterogeneous storage backends (local, S3, GCP, etc.) with a lakehouse architecture. It combines metadata management (via SQLite or Postgres), file/array storage (parquet, zarr), and a schema-based registry to enable querying and governance of datasets, models, and computational runs. The package provides lineage tracking to trace data provenance across notebooks, scripts, and agent sessions; versioning and branching for data governance; and integrations with biological ontologies and workflow tools.\n\nTypically used by research teams and biotech companies to organize experiments, manage datasets collaboratively, and ensure reproducibility. It ships as a meta-package that depends on lamindb-core and adds optional data-science dependencies. Users connect to a local or remote instance, register artifacts (files, DataFrames, AnnData objects, etc.), and query across federated datasets. The package includes a CLI for common operations (login, save, load) and a skill module for automatic tracking in AI agents.","worth_installing":"Yes, with conditions. LaminDB is actively maintained and has low install friction, making it suitable for research teams managing multimodal scientific data at scale. However, the license status is unclear\u2014verify the actual license terms before adopting in proprietary or regulated environments. The package is well-suited for collaborative biotech and academic research but requires careful vetting of compliance obligations."},"id":"lamindb","links":{"html":"https://skillfed.io/packages/lamindb","md":"https://skillfed.io/packages/lamindb.md","pypi":"https://pypi.org/project/lamindb/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-04","license_spdx":null,"license_treatment":"unclear","name":"lamindb","python_support":"supports_current","summary":"Full/meta-package module for the `lamindb` distribution."},"popularity":{"monthly_downloads":141682,"position":11235,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.9.1"}