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"The combination of disk-based change journals that are pulled by the replication targets instead of pushed by the source, makes it extremely resilient, capable of automatically recovering from elongated disruptions," said Christophe Bertrand, senior director, solutions and product marketing business continuity at Hitachi Data Systems. "Because changes are pulled by replication target arrays, valuable processing cycles are offloaded from primary arrays to secondary target arrays."
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[IMAGE] [IMAGE] Comparing data replication methods
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Type of replication
Array based
Host based
Network based
Support of heterogeneous environments
Low; only works between similar arrays
High; storage-agnostic and works with network- and direct-attached storage
High; storage array- and platform-agnostic
Performance and scalability
Depends on the storage array; very good in high-end arrays
Good; workload is spread across servers; limited scalability because of management challenges
Very good
Cost
Requires similar arrays; high entry cost; expensive for a large number of locations
No hardware required; low entry cost; cost rises proportionally to the number of servers
Requires intelligent switches or inline appliances; high entry cost; expensive for a large number of locations
Complexity
Medium to high
Low
Medium to high
Replication Modes
Synchronous and asynchronous
Asynchronous
Synchronous and asynchronous
Predominant Replication Type
Logical ...
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unit number (LUN) or volume block-level based
File-system based
LUN or volume block-level based
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