Today's cloud database systems are not designed for seamless cost-performance trade-offs for changing SLOs. Database engineers have a limited number of trade-offs due to the limited storage types offered by cloud vendors, and switching to a different storage type requires a time-consuming data migration to a new database. We propose Mutant, a new storage layer for log-structured merge tree (LSM-tree) data stores that dynamically balances database cost and performance by organizing SSTables (files that store a subset of records) into different storage types based on SSTable access frequencies. We implemented Mutant by extending RocksDB and found in our evaluation that Mutant delivers seamless cost-performance trade-offs with the YCSB workload and a real-world workload trace. Moreover, through additional optimizations, Mutant lowers the user-perceived latency significantly compared with the unmodified database.