What consistency levels does MongoDB offer?

MongoDB offers several consistency levels, with eventual, strong, and causal consistency being key components of its design. The correct answer highlights these aspects accurately.

Eventually consistent systems allow for updates to propagate through distributed systems over time, meaning that at any given moment, not all nodes may reflect the same data, but they will converge eventually. This model works well in scenarios where immediate consistency is not critical, allowing for higher availability and partition tolerance.

Strong consistency ensures that reads return the most recent write, offering a guarantee that data is always consistent across replicas at any given point in time. This level of consistency can impose some overhead and may impact performance, particularly in distributed databases.

Causal consistency is essential for operations that rely on the order of operations, ensuring that if one operation causally affects another, the first operation's effect will be visible to any subsequent operation.

Other options do mention consistency types that are not standard in the MongoDB context. For instance, strict consistency typically implies a more traditional relational database model rather than MongoDB's flexible consistency options. Unique and shared consistency does not align with MongoDB’s framework and understanding of consistency levels in distributed databases. Eventual and permanent consistency is not a recognized categorization in MongoDB's consistency model either.