The CAP theorem states that a distributed database system cannot be designed for both consistency and availability, but algorithms can significantly improve system availability while supporting strong consistency. Strong consistency guarantees that all writes to a single record will be applied in a specific order, ensuring that data remains consistent across all nodes in the cluster at any given point in time. There are different levels of consistency, with "strong consistency" being the highest level, which includes linearizable and sequential consistency models. Linearizable consistency is stricter, slower, but always returns the latest data, while sequential consistency is faster but may return stale data occasionally. Strong eventual consistency guarantees that every copy of a data item will end up with the same result without any data loss, but allows for stale reads. Eventual consistency allows for stale data and lost writes. Aerospike has developed strong consistency algorithms that provide high performance and 100% data availability during common failure scenarios, while preserving consistency and availability with minimal impact on performance.