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Asynchronous replication replicates data between two servers through a non-blocking process. This allows the primary server to process data as fast as possible without being slowed down by a secondary server or the network. It can simultaneously replicate data to multiple servers. It is ideal for replicating data between data centers.

Synchronous replication uses a blocking process to replicate data between servers to ensure both servers have persisted a transaction to their transaction logs before the primary server reports back to the application that the transaction is committed. Synchronous replication is required for high availability because only it can guarantee data is always the same on both servers at all points in time. Because it is blocking, it is not as fast as asynchronous replication.

Purchase the fastest Ethernet Network Interface Cards (NICs) compatible with your server. For high availability, purchase 2 NICs per server (we recommend 100GbE NICs).

Serial replication uses one thread to replicate data in the transaction log. Typically, a single thread cannot keep up with many database connections simultaneously writing data to a table. But if a table only has one thread writing to it, serial replication is often preferred.

Parallel replication uses many threads to replicate data simultaneously. It can keep up with multiple database connections simultaneously while writing data. In many cases, parallel replication is preferable over serial replication. Parallel replication requires more CPU to handle the additional threads it uses to process replication. Because CPU resources are limited, the number of threads is configurable. Parallel replication also has additional overhead because it does dependency checking to ensure data consistency. Dependency checking ensures that changes to the same record occur in the original transaction order. Dependent changes must be serialized. In the unusual case where many transactions have dependencies, parallel replication becomes slower than serial replication because of the overhead of dependency checking combined with the net result of serialized transactions.

Unidirectional replication is one-way replication. It is the most common type of replication and replicates data from a source to a target database server. It is simple, predictable, and has no data conflicts. It is ideal for implementing solutions such as high availability, disaster recovery, offloaded reporting, global distributed read scalability, microservice shared data, and so forth.

Bidirectional replication is two-way replication where data is replicated in both directions between database servers; thus, any data change on one server is replicated to the others. It is great for large-scale global data processing because many servers can process data in parallel and users can modify data on the server that is most closely located to them. This works best when users do not simultaneously change the same data, such as a user’s personal shopping cart. When users can change the same data, such as an application’s lookup data, this creates data conflicts that are hard for applications and users to reconcile.

Selective replication uses a filter to determine which data records in a table to replicate. Selective replication can distribute specific data to specific global data centers for regulatory compliance or to scale an application globally. It is also useful for replicating personal data to user’s mobile devices. It is also useful for sharding data within a data center. Sharding works like table partitioning except it spreads a table across database servers. In other words, it splits the data in a table into buckets and puts each bucket on a different database server. Selective replication can automatically replicate data to the proper shards.

If you are considering sharding within a data center, you will also want to consider selective replication. Sharding works like table partitioning except it spreads a table across database servers. In other words, it splits the data in a table into buckets and puts each bucket on a different database server. Selective replication can automatically replicate data to the proper shards.

Non-selective replication replicates all data in a table. This is the obvious choice when all data is necessary. However, where all data is not necessary, you can save time and performance by only replicating the data you need. Or in other cases, you may have specific business logic or even regulations to follow that limit what data can be replicated. There are also data governance advantages to be considered. In these cases, you will want to use selective replication to obtain only the data you want.