(2) GFS: GFS also has an eventual consistency model as Dynamo.It applies the operations log to recover the file and uses chunk version numbers to detect any stale replicas. Chunk server uses checksum to detect any additional data corruption due to server failure. In case of uncertainty, the data are made unavailable. Any successful operation of atomic_record_append guarantees consistency.
(3) Bigtable has its own features to support consistency. Each read or write is serializable, making it easy to maintain consistency in case of concurrent updates to the same row. Each row is copyon- write to maintain row-level consistency. Different cells in a table can contain multiple versions of the same data, indexed by timestamps. SSTables contain relatively old updates, while a buffer called memtable contains the recent updates. Updates are recorded in a commit log to recover the memtable. There is no synchronization of accesses required when reading from SSTables because SSTables are immutable.