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Merge pull request #114488 from cmendible/patch-5
Update service-bus-federation-overview.md
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articles/service-bus-messaging/service-bus-federation-overview.md

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There are numerous potential motivations for why you may want to move messages between Service Bus entities like Queues or Topics, or between Service Bus and other sources and targets.
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Compared with the similar set of patterns for [Event Hubs](../service-bus-messaging/service-bus-federation-overview.md), federation for queue-like entities is more complex because message queues promise their consumers exclusive ownership over any single message, are expected to preserve arrival order in message delivery, and for the broker to coordinate fair distribution of messages between [competing consumers](/azure/architecture/patterns/competing-consumers).
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Compared with the similar set of patterns for [Event Hubs](../event-hubs/event-hubs-federation-overview.md), federation for queue-like entities is more complex because message queues promise their consumers exclusive ownership over any single message, are expected to preserve arrival order in message delivery, and for the broker to coordinate fair distribution of messages between [competing consumers](/azure/architecture/patterns/competing-consumers).
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There are practical impediments, including the constraints of the [CAP theorem](https://en.wikipedia.org/wiki/CAP_theorem), that make it difficult to provide a unified view of a queue that is simultaneously available in multiple regions, and which allows for regionally distributed, [competing consumers](/azure/architecture/patterns/competing-consumers) to take exclusive ownership of messages. Such a geo-distributed queue would require fully consistent replication not only of messages, but also of the delivery state of every message before messages can be made available to consumers. A goal of a full consistency for a hypothetical, regionally distributed queue is in direct conflict with the key goal that practically all Azure Service Bus customers have when considering federation scenarios: Maximum availability and reliability for their solutions.
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