C4 model VS FriendlyData

• Simplicity
  The C4 model promotes a simple and clear approach for visualizing software architecture by limiting the number of diagram types and focusing on different levels of detail, making it easy to understand and use.
• Scalability
  The C4 model scales well with systems of varying complexity, offering different levels of abstraction (Context, Container, Component, and Code) tailored to different audiences and detailed needs.
• Clarity of Communication
  By dividing the representation of the system into different levels, the C4 model improves communication among stakeholders by providing the right level of detail to the right audience.
• Standardization
  The model introduces a standard way to create architecture diagrams, making it easier to maintain consistency and understandability across different teams and projects.
• Focus on Architecture
  C4 places a strong emphasis on architectural elements without becoming tied into specific tooling or technology choices, thus focusing on high-level designs rather than low-level implementation details.

Possible disadvantages

• Learning Curve
  While C4 provides a simplified approach, there is still a learning curve for those unfamiliar with its four different levels of abstraction, especially for newcomers to software architecture.
• Lack of Tool Support
  Compared to older and more established diagramming approaches, there may be limited tool support for the C4 model, which can make it harder to integrate into some existing workflows.
• Potential for Over-Simplification
  By focusing only on four levels of abstraction, there's a risk that some important details may be overlooked or oversimplified, leading to incomplete documentation for very complex systems.
• Subjectivity in Detail
  Deciding what details to include and at which level can be subjective, potentially leading to inconsistencies in diagrams if not clearly defined and standardized across a team.
• Not Comprehensive
  The C4 model focuses solely on structural organization and may not comprehensively address other architectural concerns such as behavior, performance, or data flow, requiring supplementary models or documentation.

• Ease of Use
  FriendlyData allows users to interact with databases using natural language queries, which makes it accessible for non-technical users who are not familiar with complex database query languages.
• Time-Saving
  By enabling natural language processing, FriendlyData reduces the time it takes for users to get the information they need, facilitating quicker decision-making processes.
• Integration
  FriendlyData can be integrated with various platforms and services, making it versatile for different business needs.

Possible disadvantages

• Complex Queries Limitation
  While FriendlyData is useful for simple queries, it may struggle to accurately interpret and execute more complex queries, limiting its effectiveness for advanced data analysis.
• Language Ambiguity
  Natural language processing might not always accurately interpret user queries, especially if the input is ambiguous or lacks specificity.
• Dependency on Vendor
  Relying on third-party services like FriendlyData introduces dependency on the vendor for maintenance, updates, and support, which could pose risks if the service changes or is discontinued.

Visualising software architecture with the C4 model - Simon Brown, Agile on the Beach 2019

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Tracking FriendlyData since Mar 2021.