Data Synchronization Across Data Centers

If you have your application running in different data centers in active-active manner (traffic is served by all data centers simultaneously), you might want them to use the same datasource for up-to-date data processing.
In-memory data grid could be a good solution for sharing information across multiple data centers in a real time.
And there are several ways how to build up such synchronization.

Application Running in Separate Data Centers
Application Running in Separate Data Centers

Two separate In-Memory Data Grids running in synchronized mode

All most popular In-Memory Data Grid applications support data replication over Wide Area Network (WAN).

In-Memory Data Grid Synchronization Across Data Centers
In-Memory Data Grid Synchronization Across Data Centers

Such data synchronization model is preferable because of following pross:


Single In-Memory Data Grid

If, for some reason, there is no ability to spin up a separate IMDG cluster in each of your data centers, then you can think about to have your application connected directly to the data grid running in one of the data centers:

Single In-Memory Data Grid
Single In-Memory Data Grid

However, such communication model has significant drawbacks:


Shared In-Memory Data Grid

It’s strongly not recommended to spread your data grid cluster across multiple data centers. Anyway, due to product licence restrictions you might want to have your storage nodes from one data center being communicated with storage nodes from another data center forming one single cluster:

Shared In-Memory Data Grid
Shared In-Memory Data Grid

This model could be very unstable because of network latency, and cluster’s communication between nodes from separate data centers could be interrupting. Also, inter-nodes communication is not secure, so your data could be intercepted and compromised.

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