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Vector clocks, while powerful, have limitations such as their size growing linearly with the number of nodes in the system, making them unsuitable for very large systems. Additionally, they do not provide information about events' physical time.

Vector clocks can be used to establish a causal relationship between events. If the vector timestamp of one event is less than or equal to another, across all elements, one can say that the first event causally precedes the second event.

When a node performs a local event, it increments its own vector clock element. Upon sending a message, it includes its vector clock with the message. Receiving a node updates each element in its vector clock to the maximum of the local vector and the vector received.

Two events are considered concurrent if neither event's vector clock is less than or equal to the other's vector clock. This means that neither event is causally related to the other, allowing for the possibility of concurrent operations in a distributed system.

Vector clocks are utilized for resolving conflicts in distributed databases by providing a partial ordering of writes. This ordering helps in ensuring database consistency by applying updates in a manner that adheres to the causality of events.

Vector clocks are data structures used in distributed systems for capturing the partial ordering of events based on causality, rather than time. Each element in the vector represents a timestamp from a different node in the system and is used to track the sequence of events.