Soft state is useful for efficiency because of the eventual consistency model such as short-lived user sessions, stored
aggregates and transformations on large datasets and general purpose write-through caches for files and database records.Whilst soft state is lost or made unavailable due to service instance crashes and overloads, reconstructing it through user interaction or third-tier re-access can be expensive in terms of time and resources [16]. User can afford database to be consistent over time by synchronizing information between different database nodes. They can Cache data (soft state) and use it later to increase the database response time. They may be having a number of database nodes with distributed data to be highly available (partition tolerance).