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.
$NaN
Per 1 ms
Salesforce Lightning Platform
Score 8.0 out of 10
N/A
Salesforce Platform is designed for building and deploying scalable cloud applications with managed hardware provisioning and app stacks. It provides out-of-the-box tools and services to automate business processes, integrate with external apps, and provide responsive layouts and more.
$25
Per User Per Month
Pricing
AWS Lambda
Salesforce Lightning Platform
Editions & Modules
128 MB
$0.0000000021
Per 1 ms
1024 MB
$0.0000000167
Per 1 ms
10240 MB
$0.0000001667
Per 1 ms
Starter
$25.00
Per User Per Month
Plus
$100.00
Per User Per Month
Offerings
Pricing Offerings
AWS Lambda
Salesforce Lightning Platform
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Community Pulse
AWS Lambda
Salesforce Lightning Platform
Features
AWS Lambda
Salesforce Lightning Platform
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.
We use Salesforce Lightning Platform in everyday business as sales coordinators. By using this tool, we are able to send new requests to clients and communicate regarding pending proposals in real-time. This also tool holds many of our client accounts where we are able to monitor their sales and revenue.
Reporting and Dashboards are thorough and can show a wealth of important data to inform and scale processes. It's helpful in a high volume sales cycle to be able to quickly identify weak points in performance and productivity so that adjustments can be made.
Highly customizable. We are able to customize just about everything which allows us to track very specific things and in theory create better efficiency.
Parent/Child account hierarchy exists which is helpful.
Contact records can be associated with multiple accounts and opportunities. This, in theory, should minimize duplicates and mismanagement of contacts.
Console helps a lot with data nesting. Having a fairly comprehensive look at an account without searching through various tabs and sections speeds up an otherwise cumbersome platform.
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.
UI can be quite complex, but the more that is required will bring more complexity. Can handle complexity and variety very well, but makes ground-level views harder when not knowing full extent of functionality. Finding new functionalities can be difficult to pinpoint on some pages
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.
Salesforce's support is top-notch. They have subject-matter experts that are accessible at all times to address needs as they come up. They let you know in advance when there are system updates and enhancements so that you are prepared for upcoming changes. I've never had an issue that wasn't addressed immediately when reaching out for support.
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
We were previously using an older version prior to it becoming Salesforce Lightning Platform so we were well adverse on the advantages of using a CRM, to begin with. It made sense to convert to Salesforce Lightning Platform after we were given a free trial of the platform. Certain reps were chosen to experiment with it and from there a decision was made to move forward. We've been customers ever since.
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.