Data Synchronisation
Explore key concepts of data synchronization in distributed systems, including the challenges of storing data in multiple places, issues with dual writes, and how distributed transaction protocols address atomicity and isolation problems to ensure consistency.
We'll cover the following...
The need to store data in multiple places
There are cases where we need to store the same data in multiple places and potentially different forms. These are also referred to as materialized views. Below are some examples of such cases:
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Data that resides in a persistent datastore also needs to be cached in a separate in-memory store so that read operations can be processed from the cache with lower latency. Write operations need to update both the persistent datastore and the in-memory store.
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Data stored in a distributed key-value store must also be stored in a separate datastore that ...