LaminDB: Manage data & analyses

Curate, store, track, query, integrate, and learn from biological data.

Modular configurable data & analysis platform for hybrid R&D organizations to

1. query low- and high-dimensional data by biological entities ⸻ organize data in the hypothesis space

2. query data by provenance (users, notebooks, pipelines, instruments, etc.) ⸻ track it all

3. share data within and across organizations in an interoperable, reusable way ⸻ no cleaning anymore

with

1. an intuitive API to connect data and analytics infrastructure

2. zero lock-in danger due to an open-source & multi-cloud stack

3. a tool to easily manage schema module migrations in a changing R&D environment

4. support for learning from data across measured → relevant → derived features

5. support for fast-paced iterations and “development data” through data versioning, quality & integrity flags

LaminDB is a distributed data management system similar to how git is a distributed version control system. Each LaminDB instance is a data warehouse with storage (local directory, S3, GCP, Azure) and a SQL database (SQLite, Postgres, BigQuery) for querying it.

Install:

pip install lamindb

Get started:

• Tutorials walk you through setup and usage of the platform.

• Explore real-world examples.

• Browse the API reference.

• If you get stuck, see guides for edge cases & errors.

References:

• See lamin.ai/docs for an overview of associated open-source modules.

• Reach out to learn about modules that connect your assays, pipelines, instruments & workflows within our data platform enterprise offer.

• Read the following reports to learn about technology underlying LaminDB: …