A busy developer needs to understand the underlying database storage engine when evaluating operational databases, focusing on flexibility, consistency guarantees, scalability, fault tolerance, latency, throughput, and manageability. Two popular types of storage engines are B-tree based and LSM tree based, each with its pros and cons. B-trees prioritize read performance but struggle with write performance due to maintaining a well-ordered data structure. In contrast, LSM trees focus on sequential writes for high-performance workloads with large data volumes, leveraging tiered storage mechanisms. While LSM engines exhibit higher CPU resources during read operations, these issues are mitigated in practice. Both types of engines have been adopted by popular databases and NoSQL systems, including Oracle DB, MS SQL Server, MongoDB, Apache Cassandra, Elasticsearch, and InfluxDB.