When choosing between range-based and hash-based partitioning, hash-based is advised for uniform distribution and to avoid hotspots. Range-based is suitable for queries involving specific data ranges. The decision depends on the access patterns and distribution goals.

Version control handles rollback by allowing users to manually revert changes to a specific commit. This ensures flexibility in undoing undesirable modifications and restoring the data model to a previous state while maintaining a record of version history.

The primary data structure used in document-based modeling is JSON (JavaScript Object Notation). JSON allows for flexible and hierarchical data representation, making it suitable for storing and retrieving complex data structures. Document databases leverage this format to organize and query data efficiently.

Yes

The primary focus of Dimensional Modeling is optimizing performance for retrieval and analysis. Unlike normalization, which aims for data integrity through minimizing redundancy, Dimensional Modeling prioritizes efficient querying and reporting for analytical purposes. This involves designing structures that align with how users typically access and analyze data in a data warehouse.

The data compression ratio is typically not considered when deciding how to partition data. Partitioning decisions are primarily based on factors such as data distribution, query performance, and security requirements, but compression considerations are addressed separately.

In Forward Engineering, the process begins with a Logical Data Model. This model represents the abstract structure of the data without concerning itself with the physical implementation. It serves as a bridge between the high-level conceptual model and the detailed physical model.

For this scenario, a One-to-One relationship is appropriate. Each appointment is associated with one patient and one doctor. It ensures that each appointment is uniquely linked to a specific patient and doctor, avoiding data redundancy.

Eventual Consistency in NoSQL databases sacrifices immediate consistency in favor of high availability and partition tolerance. It allows replicas of data to become consistent over time, ensuring that all replicas will eventually converge to the same value. This trade-off is suitable for systems where availability is crucial, and temporary inconsistencies can be tolerated.

The purpose of Database Indexing is to improve query performance by organizing table data based on predefined criteria. Indexing creates a data structure that allows for faster retrieval of information, especially in large databases.