Block storage is often selected to host high-performance transactional databases in both cloud and on-premises environments. Which of the following characteristics best explains why block storage fits this workload?
It presents volumes to the operating system as raw disks whose data is divided into fixed-size blocks that can be addressed over protocols like iSCSI or NVMe/TCP, delivering consistently low I/O latency.
It stripes data across nodes using erasure coding to reduce capacity consumption, accepting higher write latency suited mainly for cold-archive workloads.
It exposes data through a hierarchical directory path over shared-file protocols such as NFS or SMB so multiple users can concurrently edit common files.
It stores each dataset as immutable objects along with extensive custom metadata and automatically replicates or erasure-codes those objects across geographic regions to maximize durability.
Block storage divides data into fixed-size chunks (blocks) that are addressed directly by the operating system using low-level protocols such as iSCSI or NVMe/TCP. Because the host treats the volume like a locally attached disk, the database can format the device with its own file system and issue random reads and writes with sub-millisecond latency-ideal for OLTP workloads.
The other statements describe capabilities of other storage types:
Object storage keeps data as immutable objects with rich metadata and often uses replication or erasure coding across regions to maximize durability; this design trades latency for scalability and resilience.
File storage exposes a hierarchical directory structure over protocols like NFS or SMB for shared user access, which adds additional overhead compared with raw block devices.
Erasure-coded, capacity-optimized architectures are tuned for archival or infrequently accessed data, not latency-sensitive transaction processing.
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