Virtual synchrony: This computational model is used when a group of processes cooperate to replicate the in-memory data or to coordinate actions. The model defines a new distributed entity called a process group. A process can join a group, which is much like opening a file; the process is added to the group, but is also provided with a checkpoint containing the current state of the data replicated by group members. Processes can then send events to the group and will see incoming events in the identical order, even if events are sent concurrently. Membership changes are handled as a special kind of platform-generated event that delivers a new membership view to the processes in the group.
Levels of performance vary widely depending on the model selected. Transactional replication is slowest, at least when one-copy serializability guarantee is desired. Virtual synchrony is the fastest of the three models, but handling of failures is less rigorous than in the transactional model. State machine replication lies somewhere in between; the model is faster than transactions, but much slower than virtual synchrony.
The virtual synchrony model is popular because it allows the developer to use either active or passive replication. In contrast, the state machine replication and transactional replication are highly constraining and are often embedded into products at layers where end-users could not be able to access them.
Database replication can be used on many database management systems, usually with a master/slave relationship between the original and the replicated copies. The master logs the updates, which then ripple through to the slaves. Each slave outputs a message stating that it has received the update successfully, thus allowing the sending (and potentially re-sending until successfully applied) of subsequent updates.
In multi-master replication the updates can be submitted to any database node which then ripple through to other servers, is often desired, but introduces substantially increased costs and complexity which may make it impractical in some situations. The most common challenge that exists in multi-master replication is transactional conflict prevention or resolution. Most synchronous or eager replication solutions perform conflict prevention, while asynchronous solutions have to perform conflict resolution. For instance, if a record is changed on two nodes simultaneously, an eager replication system would detect the conflict before confirming the commit and aborting one of the transactions. A lazy replication system would allow transactions to commit as well as run a conflict resolution during resynchronization. The resolution of such a conflict may be based on a timestamp of the transaction, on the hierarchy of the origin nodes or on much more complex logic, which decides consistently on all nodes.
Database replication becomes difficult when it scales up. Usually, the scale up goes with two dimensions, horizontal and vertical: horizontal scale up has more data replicas, vertical scale up has data replicas located further away in distance. Problems raised by the horizontal scale up can be alleviated by a multi-layer multi-view access protocol. Vertical scale up runs into less trouble since internet reliability and performance are improving.
The active storage replication is usually implemented by distributing updates of a block device to several physical hard disks. Thus, any file system that is supported by the operating system can be replicated without modification, as the file system code works on a level above the block device driver layer. It is implemented either in hardware or in software.
The most basic method is disk mirroring, typical for locally-connected disks.
Notably, the storage industry narrows the definitions, so mirroring is a local operation. A replication is extendable across a computer network, so the disks can be located in physically distant locations. The purpose is to avoid damage done by, and improve availability in case of local failures or disasters.
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