"MotherDuck: Collaborative DuckDB in the Cloud for Teams" MotherDuck brings DuckDB’s fast, embedded analytics model into a collaborative, cloud-backed workflow—without surrendering the ergonomics that make DuckDB beloved by power users. This book is written for experienced engineers, analytics platform builders, and data teams who want the performance and portability of DuckDB while gaining the reliability, governance, and sharing mechanics needed for real multi-user work. You’ll build a precise mental model of how local DuckDB state interacts with MotherDuck’s remote catalogs via the `md:` protocol, then make connectivity and authentication “boringly reliable” across laptops, notebooks, CI, and orchestrators. The book goes deep on token operations and hygiene, creating and migrating shared databases, and the centerpiece collaboration primitive: snapshot-based shares that enable reproducible data releases, controlled updates, and safe rollback. You’ll also learn organization-level sharing controls and discoverability practices, plus secure access to external object storage with secrets management, rotation, and least-privilege ingestion patterns. Prerequisites include strong SQL, comfort with DuckDB clients (CLI/Python), and production-minded operational habits. The differentiator is a team-first approach: conventions, decision criteria, and failure-mode coverage that turn ad-hoc analytics into durable, governable shared data products.