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Database Concepts

MotherDuck Architectural Concepts​

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MotherDuck is a cloud-native data warehouse, built on top of DuckDB, a fast in-process analytical database. It inherits some features from DuckDB that present opportunities to think differently about data warehousing methods in order to achieve high levels of performance and simplify the experience.

  • Isolated Compute Tenancy: Each user is allocated their own "duckling," which is an isolated piece of compute that sits on top of the MotherDuck storage layer. MotherDuck is designed this way to lessen contention between users, which is a common challenge with other data warehouses. Each duckling had under 100ms of cold start time as MotherDuck keeps Ducklings on warm standby.

  • Aggressively Serverless: Unlike conventional data warehouses, DuckDB automatically parallelizes the work that you send to it. The implication of this is that scheduling multiple queries at-a-time does not meaningfully increase throughput, as DuckDB has already parallelized the workload across all available resources.

  • Database level security model: It has a simplified access model - users either have access to an entire database, or nothing at all. As a result, users will interact with data frequently at the database level. This is unusual when compared to other databases, which often treat multiple database files as single concepts from an interactivity perspective.

  • Database Sharing: MotherDuck separates storage and compute, which means that one user cannot see another's writes into a database until that database is updated to that user. As such, it has its own concept called "SHARES" within Organizations, which are zero-copy clones of the main database for read-only use, enabling high scalability of analytics workloads.

  • Dual Execution: Every MotherDuck client is also a DuckDB engine, so you can efficiently query local data and (JOIN, UNION) with data that's stored in your MotherDuck data warehouse. The query planner automatically decides the best place to execute each part of your query.