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Data residency

Data residency is a requirement or practice governing the geographic locations or jurisdictions in which data may be stored or processed.

How 2 Manning books explain it

Architecting an Apache Iceberg Lakehouse

Data residency is the requirement that data be stored or processed within specified geographic or jurisdictional boundaries.

How it is used
Constrains lakehouse storage, catalog, and query architecture when organizations must satisfy geographic, privacy, or regulatory boundaries.
How deep it goes
Explains placement, replication, encryption, auditing, and query enforcement, but stops short of specifying one universal deployment pattern.
Examples
Uses regional healthcare datasets, jurisdiction-aware Iceberg tables, and hybrid bank storage spanning cloud and on-premises object stores.
What you can do after
Operate/configure storage, catalogs, and query paths so regulated data remains localized and compliance evidence remains auditable.

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MongoDB 8.0 in Action, Third Edition

A data residency policy specifies the geographic locations in which data may be stored or processed.

How it is used
Guides Atlas deployment choices when applications require regional data locality, regulatory compliance, low latency, or high availability.
How deep it goes
Explains geopartitioning, zones, region roles, and customer configuration, but does not provide command-level setup instructions.
Examples
Uses Atlas Global Clusters, regional shards, and Highest Priority, Electable, and Read-only region assignments as implementation examples.
What you can do after
Configure Atlas Global Clusters to keep data in designated regions while supporting regional reads, writes, and failover.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.