Diskbased

Diskbased refers to computing systems that primarily use non-volatile disk storage as the main data repository, rather than relying on volatile main memory. In practice, diskbased storage systems keep data on hard disks or solid-state drives and load portions into memory as needed. This contrasts with in-memory systems where most active data resides in RAM for fast access.

Characteristics of diskbased systems include higher latency and slower random access compared with RAM, but much larger capacity and lower cost per byte. They emphasize persistence and durability, as data remains on disk across power cycles. Performance depends on disk throughput, seek times, caching, and I/O scheduling; modern systems use a memory cache and prefetching to mitigate latency.

Applications and domains for diskbased approaches include traditional relational databases, data warehousing, log processing, archival storage, and large-scale file systems. Many systems combine disk storage with fast caches or hybrid architectures to balance latency and capacity. With growing use of SSDs, diskbased storage can achieve substantial throughput while retaining durability and cost benefits.

Optimization techniques involve indexing, query optimization, data partitioning, batching of I/O, and asynchronous I/O. File systems and databases may employ write-ahead logging, compression, and data deduplication to improve efficiency on disk. Diskbased solutions remain relevant where datasets exceed available RAM or where long-term persistence is required.

See also: disk I/O, storage hierarchy, in-memory database, persistent memory, data deduplication.