Master Vim VS SQL Server 2017

• Efficiency
  Vim allows users to perform text editing using keyboard shortcuts, which can significantly speed up the editing process once the shortcuts are mastered.
• Lightweight
  Vim is a highly efficient text editor that requires minimal system resources, making it suitable for use on older hardware and in low-resource environments.
• Customizability
  Vim offers extensive customization options through its scripting language and plugins, allowing users to tailor the editor to fit their specific needs.
• Versatility
  Vim can be used for a wide range of tasks beyond simple text editing, such as coding and prose writing, due to its powerful features and plugins.
• System Integration
  Vim is available on most Unix-based systems, including macOS and Linux, and can be accessed and used in terminal environments, which integrates well with command-line workflows.

Possible disadvantages

• Steep Learning Curve
  Vim's extensive set of commands and mode-based editing requires time and practice to master, which can be challenging for new users.
• Minimal User Interface
  Vim's interface is minimal and non-intuitive by modern standards, potentially making it difficult for users accustomed to graphical user interfaces.
• Limited New User Documentation
  While there is ample documentation available for Vim, the initial introduction for new users can be overwhelming, and they may find it difficult to locate beginner-friendly resources.
• Dependency on Keyboard
  Vim relies heavily on keyboard shortcuts, which can be difficult for users who prefer or need to use a mouse or other input methods.
• Customization Overhead
  While Vim is highly customizable, setting it up with the desired configuration and plugins can be time-consuming and may require ongoing maintenance.

• Cross-Platform Support
  SQL Server 2017 offers cross-platform support, enabling it to run on Windows, Linux, and Docker containers, providing flexibility and integration into various environments.
• Graph Database Capabilities
  Introduces graph database capabilities, allowing the modeling of complex data relationships easily and efficiently, expanding its use cases.
• Advanced Analytics
  Integrates with Microsoft R and Python services, facilitating advanced analytics and machine learning directly within the database, which helps organizations to perform sophisticated data analysis.
• Adaptive Query Processing
  Includes adaptive query processing features to optimize query performance automatically, improving application speed and efficiency.
• Enhanced Security
  SQL Server 2017 continues to enhance security with features like Always Encrypted, Dynamic Data Masking, and Row-Level Security to protect sensitive data.

Possible disadvantages

• Cost
  Licensing and support costs for SQL Server can be relatively high, particularly for enterprise editions, which may not be cost-effective for smaller organizations.
• Complexity
  SQL Server 2017 includes a vast array of features and configurations that can introduce complexity, requiring substantial expertise to manage and optimize.
• Resource Intensive
  Requires significant system resources for optimal performance, which may necessitate additional investment in hardware to operate efficiently at scale.
• Limited NoSQL Functionality
  While SQL Server 2017 introduces some NoSQL features through its support for JSON and graph databases, it still lags behind dedicated NoSQL databases in terms of flexibility and scalability for unstructured data.
• Version-Specific Features
  Some advanced features are only available in the latest versions or specific editions, which may necessitate upgrades or specific licensing to access the full capabilities, leading to additional expenses.

MASTER VIM with this interactive course (vim.so review)

SQL Server 2017 – Everything you need to know

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Tracking SQL Server 2017 since Mar 2021.