Database storage engines, such as B-tree and LSM, have different designs that optimize for either read or write performance, and also consider consistency, transactions, concurrency control, compaction, and compression. Monolithic databases prioritize strong consistency and ACID transactions, while distributed databases like NoSQL databases often sacrifice consistency for availability. Concurrency control mechanisms, such as MVCC, play a crucial role in handling concurrent requests, with SQL databases typically supporting Snapshot Isolation and Serializable levels, while NoSQL databases like Cassandra and DynamoDB use eventual consistency and last-writer-wins semantics. Compaction and compression are also important aspects of database storage engines, with LSM engines offering multiple compaction strategies and compression algorithms, and B-tree engines susceptible to fragmentation that hinders compression. Understanding these factors is essential for a complete understanding of the design of database storage engines.