Strong consistency and Eventual consistency are two basic principles that are being used in the creation of systems, especially distributed databases and systems.

• Strong consistency means that all nodes in a distributed system reflect the same data at once after any update, which gives immediate consistency.
• Eventual consistency, on the other hand, permits temporary instability of nodes, however, it promises that all nodes will eventually be updated.

These consistency models affect system performance, availability, and user experience, and therefore, choosing them or implementing them in a solution directly affects system architecture.

Strong vs. Eventual Consistency

What is Strong Consistency?

The strong consistency makes it possible for any read operation on a distributed data system to result in the most up-to-date data. This means that once a write operation is confirmed, every subsequent read operation will always reflect the said change, even if operations are carried out in different nodes in the system. It ensures that all copies of the data are consistent and up to date in the entire system and all replicas are also good. This consistency model is useful for application development since it gives predictable and reliable results from the data. Below are some features of strong consistency:

• Linearizability: A process seems to happen in a series of steps, and as a result, real-time data is accessed in order and continuously updated.
• Read-after-Write Consistency: Makes sure that if a write is accepted, the next read will include that write.
• Single Copy Consistency: It acts as if there is only a copy of data, which avoids the copies’ inconsistencies.
• Global Ordering of Operations: All the operations are made under a global order thus presenting a clear and ordered sequence of operations.
• Atomicity: Consistent data updates are achieved because all parts of a write operation are made in one atomic transaction to all replicas.

What is Eventual Consistency?

Eventual consistency in system design is a consistency model that stipulates that if the nodes of a distributed system are allowed enough time wherein no new updates are performed, then, all the replicas of a materialization of a data item will eventually be the same. It does not ensure the consistency of views after writing, as strong consistency does, but has the advantage of being able to cope better in certain cases. Below are some features if eventual consistency:

• Convergence: If there are no new updates for a sufficient amount of time, all replicas will be equal to each other.
• High Availability: High availability of the system where reads and writes can go on even in the event of network splits.
• Scalability: It can easily scale out to multiple nodes because it is fine with being a little inconsistent.
• Temporary Inconsistency: This makes it possible to have temporary time differences between replicas through synchronization.
• Asynchronous Updates: Changes are made to replicas asynchronously which in turn, eliminates latency by returning utmost results promptly.

Strong vs. Eventual Consistency in System Design

Below are the differences between strong and eventual consistency in system design: