AWS Lambda VS Microsoft SQL

• Scalability
  AWS Lambda automatically scales your application by running your code in response to each trigger. This means no manual intervention is required to handle varying levels of traffic.
• Cost-effectiveness
  You only pay for the compute time you consume. Billing is metered in increments of 100 milliseconds and you are not charged when your code is not running.
• Reduced Operations Overhead
  AWS Lambda abstracts the infrastructure management layer, so there is no need to manage or provision servers. This allows you to focus more on writing code for your applications.
• Flexibility
  Supports multiple programming languages such as Python, Node.js, Ruby, Java, Go, and .NET, which allows you to use the language you are most comfortable with.
• Integration with Other AWS Services
  Seamlessly integrates with many other AWS services such as S3, DynamoDB, RDS, SNS, and more, making it versatile and highly functional.
• Automatic Scaling and Load Balancing
  Handles thousands of concurrent requests without managing the scaling yourself, making it suitable for applications requiring high availability and reliability.

Possible disadvantages

• Cold Start Latency
  The first request to a Lambda function after it has been idle for a certain period can take longer to execute. This is referred to as a 'cold start' and can impact performance.
• Resource Limits
  Lambda has defined limits, such as a maximum execution timeout of 15 minutes, memory allocation ranging from 128 MB to 10,240 MB, and temporary storage up to 512 MB.
• Vendor Lock-in
  Using AWS Lambda ties you into the AWS ecosystem, making it difficult to migrate to another cloud provider or an on-premises solution without significant modifications to your application.
• Complexity of Debugging
  Debugging and monitoring distributed, serverless applications can be more complex compared to traditional applications due to the lack of direct access to the underlying infrastructure.
• Cold Start Issues with VPC
  When Lambda functions are configured to access resources within a Virtual Private Cloud (VPC), the cold start latency can be exacerbated due to additional VPC networking overhead.
• Limited Execution Control
  AWS Lambda is designed for stateless, short-running tasks and may not be suitable for long-running processes or tasks requiring complex orchestration.

• Comprehensive Feature Set
  SQL Server offers a wide range of features including advanced analytics, in-memory capabilities, robust security measures, and integration services.
• High Performance
  With in-memory OLTP and support for persistent memory technologies, SQL Server provides high transaction and query performance.
• Scalability
  SQL Server can scale from small installations on single machines to large, data-intensive applications requiring high throughput and storage.
• Security
  SQL Server offers advanced security features like encryption, dynamic data masking, and advanced threat protection, ensuring data safety and compliance.
• Integrations
  It easily integrates with other Microsoft products such as Azure, Power BI, and Active Directory, providing a cohesive ecosystem for enterprise solutions.
• Developer Friendly
  It supports a wide range of development tools and languages including .NET, Python, Java, and more, making it highly versatile for developers.
• High Availability
  Features like Always On availability groups and failover clustering provide high availability and disaster recovery options for critical applications.

Possible disadvantages

• Cost
  SQL Server can be expensive, particularly for the Enterprise edition. Licensing costs can add up quickly depending on the features and scale required.
• Complexity
  Due to its comprehensive feature set, SQL Server can be complex to configure and manage, requiring skilled administrators and developers.
• Resource Intensive
  SQL Server can be resource-intensive, requiring substantial hardware resources for optimal performance, which can increase overall operational costs.
• Windows-Centric
  While SQL Server can run on Linux, it is primarily optimized for and tightly integrated with the Windows ecosystem, which may not suit all organizations.
• Vendor Lock-In
  Being a proprietary solution, it can cause vendor lock-in, making it challenging to switch to alternative database systems without significant migration efforts.

AWS Lambda Vs EC2 | Serverless Vs EC2 | EC2 Alternatives

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Tracking Microsoft SQL since Mar 2021.