A composite key consists of multiple columns to uniquely identify a record, whereas a single-column key uses only one column for this purpose. Composite keys are often used when a single column cannot guarantee uniqueness.

Vertical partitioning involves splitting tables based on columns, which means dividing a table into smaller, more manageable parts based on specific columns. This can be beneficial for improving query performance and managing data more efficiently.

The process of aggregating data from various sources into a fact table is known as Aggregation. This involves summarizing and combining data to provide a more comprehensive view for analysis. Aggregation is a key step in data warehousing, enabling efficient reporting and analysis of large datasets.

In graph databases, edges often have labels to denote the type or nature of the relationship. Labels provide a way to categorize relationships, making it easier to understand the semantics of connections between nodes. This enhances the readability and querying capabilities of graph databases.

UML and SQL serve different purposes in data modeling. UML is a visual modeling language primarily used for modeling software systems, focusing on object-oriented concepts such as classes, objects, and relationships. SQL, on the other hand, is a database query language used for managing and manipulating relational databases. While UML can represent the structure and behavior of a system, SQL is used for defining and querying the data stored in databases.

The main purpose of a fact table in Dimensional Modeling is to store quantitative data, typically numerical values that represent business facts. These facts are often measures such as sales, revenue, or quantities. Fact tables are linked to dimension tables, providing context and additional details for the stored facts, facilitating meaningful analysis.

Partitioning in database management serves the purpose of organizing large datasets into smaller, more manageable segments. It helps in improving query performance, data availability, and maintenance tasks by dividing the data into logical partitions based on predefined criteria such as range or hash values.

Collaboration features in ER diagram tools for intermediate users are significant as they facilitate teamwork and concurrent design. Multiple team members can work on the same project simultaneously, ensuring efficient collaboration and reducing the chances of conflicts in the database design process.

Modality in a relationship between entities indicates the presence or absence of entities in the relationship. It describes whether a related entity is optional or mandatory, providing insights into the completeness of the relationship.

Techniques like vector clocks are commonly used to achieve eventual consistency in NoSQL databases. Vector clocks help in tracking and ordering updates across distributed nodes, enabling eventual convergence of data while allowing for some level of asynchrony.

In data warehousing, Dimensional Modeling involves aggregating data at a higher level of granularity. It focuses on organizing data in a way that supports efficient querying and reporting, often using fact and dimension tables to represent business processes.

Tools like ER Diagram Tools and Database Design Tools play a crucial role in visualizing and designing database structures during both Forward and Reverse Engineering. They assist in creating visual representations, ensuring efficient communication between stakeholders and aiding in the overall design process.