  Context: The efficient processing of Big Data is a challenging task for SQL
and NoSQL Databases, where competent software architecture plays a vital role.
The SQL Databases are designed for structuring data and supporting vertical
scalability. In contrast, horizontal scalability is backed by NoSQL Databases
and can process sizeable unstructured Data efficiently. One can choose the
right paradigm according to the organisation's needs; however, making the
correct choice can often be challenging. The SQL and NoSQL Databases follow
different architectures. Also, the mixed model is followed by each category of
NoSQL Databases. Hence, data movement becomes difficult for cloud consumers
across multiple cloud service providers (CSPs). In addition, each cloud
platform IaaS, PaaS, SaaS, and DBaaS also monitors various paradigms.
Objective: This systematic literature review (SLR) aims to study the related
articles associated with SQL and NoSQL Database software architectures and
tackle data portability and Interoperability among various cloud platforms.
State of the art presented many performance comparison studies of SQL and NoSQL
Databases by observing scaling, performance, availability, consistency and
sharding characteristics. According to the research studies, NoSQL Database
designed structures can be the right choice for big data analytics, while SQL
Databases are suitable for OLTP Databases. The researcher proposes numerous
approaches associated with data movement in the cloud. Platform-based APIs are
developed, which makes users' data movement difficult. Therefore, data
portability and Interoperability issues are noticed during data movement across
multiple CSPs. To minimize developer efforts and Interoperability, Unified APIs
are demanded to make data movement relatively more accessible among various
cloud platforms.
