Greenplum Unified Analytics Platform (UAP) - Getting Started with Greenplum for Big Data Analytics - page 35

Shared disk data architecture refers to an architecture where there is a data disk that
holds all the data and each node in the cluster accesses this data for processing.
Any data operations can be performed by any node at a given point in time and in
case two nodes attempt persisting/writing a tuple at the same time, to ensure con-
sistency, a disk-based lock or intended lock communication is passed on thus affect-
ing the performance. Further with increase in the number of nodes, contention at the
database level increases. These architectures are write limited as there is a need
to handle the locks across the nodes in the cluster. Even in case of the reads, parti-
tioning should be implemented effectively to avoid complete table scans.
Shared memory data architecture
Have a look at the following figure which gives an idea about shared memory data
architecture:
In memory, data grids come under the shared memory data architecture category. In
this architecture paradigm, data is held in memory that is accessible to all the nodes
within the cluster. The major advantage with this architecture is that there would be
no disk I/O involved and data access is very quick. This advantage comes with an
additional need for loading and synchronizing data in memory with the underlying
data store. The memory layer seen in the following figure can be distributed and loc-
al to the compute nodes or can exist as data node.