AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
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Per 1 ms
Azure SQL Managed Instance
Score 8.8 out of 10
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Azure SQL Managed Instance is a scalable cloud database service that combines SQL Server database engine compatibility with a fully managed and evergreen platform as a service.
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Pricing
AWS Lambda
Azure SQL Managed Instance
Editions & Modules
128 MB
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Per 1 ms
1024 MB
$0.0000000167
Per 1 ms
10240 MB
$0.0000001667
Per 1 ms
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AWS Lambda
Azure SQL Managed Instance
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No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
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AWS Lambda
Azure SQL Managed Instance
Features
AWS Lambda
Azure SQL Managed Instance
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.
Data management scenarios where there is a strong need to provide dynamic context for web based applications. Also can work as an infrastructure piece for ticketing systems without relying on another set of database software. The ease of importing data from Microsoft Excel &/or .csv files makes this really easy to use when importing data into the managed instance.
Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.
it runs the workload very well without causing any issues to the business. there are many applications running on Azure SQL Managed Instances in my organization. Most users are happy with its performance. Is able to provide good dashboard for the visibility of the workload. Can add cpu without a downtime to deal with high workload.
Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions
Azure to our enviironment where we have everything integrated stacks up far better than MySQL where we would have to reinvent and use everything to fit a MySQL environment including the data and the commands within that data. Furthermore, doesn't work really well on SQL Management Studio which makes it completely useless for what we are trying to do.
Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.
