  Cloud key-value (KV) stores provide businesses with a cost-effective and
adaptive alternative to traditional on-premise data management solutions. KV
stores frequently consist of heterogeneous clusters, characterized by varying
hardware specifications of the deployment nodes, with each node potentially
running a distinct version of the KV store software. This heterogeneity is
accompanied by the diverse metadata that they need to manage. In this study, we
introduce MetaHive, a cache-optimized approach to managing metadata in
heterogeneous KV store clusters. MetaHive disaggregates the original data from
its associated metadata to promote independence between them, while maintaining
their interconnection during usage. This makes the metadata opaque from the
downstream processes and the other KV stores in the cluster. MetaHive also
ensures that the KV and metadata entries are stored in the vicinity of each
other in memory and storage. This allows MetaHive to optimally utilize the
caching mechanism without extra storage read overhead for metadata retrieval.
We deploy MetaHive to ensure data integrity in RocksDB and demonstrate its
rapid data validation with minimal effect on performance.
