| Optimal workloads | Relational databases are designed for online transaction processing (OLTP) applications with high stability and are suitable for online analytical processing (OLAP). | NoSQL databases are designed for data access patterns, including low latency applications. The NoSQL search database is designed for analysis of incomplete structured data. |
| Data model | The relational model normalizes data into tables made up of rows and columns. Diagrams clearly specify tables, rows, columns, indexes, relationships between tables, and other database elements. The database will enforce referential integrity in relationships between tables. | NoSQL databases offer a variety of data models such as key-value, document, and graph, optimized for optimal performance and scale. |
| Performance | Performance often depends on the drive’s subsystem. Usually, optimization of queries, indexes, and table structure is required for maximum performance. | Performance is often viewed as a function of implicit hardware cluster size, network latency, and application calling. |
| Scale | Relational databases typically scale by increasing the computing power of their hardware or by adding copies of read-only workloads. | NoSQL databases are often highly fragmented because key-value access patterns are scalable using a distributed architecture to increase throughput, providing consistent performance at near-scale. like unlimited. |
| APIs | Data storage and retrieval requirements are communicated using queries that are consistent with the structured query language (SQL). These queries are analyzed and executed by the relational database. | The object-based API allows application developers to easily store and retrieve data structures in memory. Fragment key looks for key-value pairs, column sets, or incomplete structured text containing chained application objects and properties. |
