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
Google App Engine
Score 8.2 out of 10
N/A
Google App Engine is Google Cloud's platform-as-a-service offering. It features pay-per-use pricing and support for a broad array of programming languages.
$0.05
Per Hour Per Instance
Agentforce Sales
Score 8.7 out of 10
N/A
Salesforce' Agentforce Sales (formerly Salesforce Sales Cloud) is the company's flagship CRM platform. The AI CRM for Sales features data built right in.
$25
per month
Pricing
AWS Lambda
Google App Engine
Salesforce Agentforce Sales
Editions & Modules
128 MB
$0.0000000021
Per 1 ms
1024 MB
$0.0000000167
Per 1 ms
10240 MB
$0.0000001667
Per 1 ms
Starting Price
$0.05
Per Hour Per Instance
Max Price
$0.30
Per Hour Per Instance
Starter
$25.00
per month per user
Professional
$80.00
per month per user
Enterprise
$165.00
per month per user
Unlimited
$330.00
per month per user
Agentforce 1 Sales
$550
per month per user
Offerings
Pricing Offerings
AWS Lambda
Google App Engine
Agentforce Sales
Free Trial
No
No
Yes
Free/Freemium Version
No
Yes
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Optional
Additional Details
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—
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More Pricing Information
Community Pulse
AWS Lambda
Google App Engine
Salesforce Agentforce Sales
Considered Multiple Products
AWS Lambda
Verified User
Engineer
Chose AWS Lambda
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 …
For our organization, we selected Google App Engine which provides a reliable and efficient way to create and deploy apps moreover it supports a lot of languages and provides automatic debugging of code which enables us to deploy code to production as soon as development is …
If you have a small team which is also responsible for development of the product then surely go for it. And if you have a larger team with dedicated person to take care of deployments. Go for cheaper options such as compute engine or AWS (be sure to do your research on pricing …
You can create and scale Kubernetes clusters quickly, but you have to keep an eye on that cluster. In-App Engine, you don't have to worry about infrastructure, but in some scenarios, Kubernetes fits better.
Azure App Service is in par with Google App Engine although you may want to use Azure App Service if you are integrating with other Microsoft IT components, for example SQL Server. Google App Engine is great when in long run, you will be using Google cloud components, for …
Google App Engine is very easy to use and mostly up to date makes it compatible with all old and new devices. The applications are very interactive and the prices are accessible for most users. The prices tend to get slightly expensive as we head on towards higher …
The two giants are Google and Amazon. Both are very similar however Google App Engine allows you to deploy your web applications through platforms like Python where as if you're using AWS, you have full control on the operating system services. Google is good because you pay as …
I think that Microsoft and Amazon are simply investing more in their offerings, and there are a bunch of cool PaaS solutions out there as well. Google App Engine is solid, and is probably the right choice for some projects. But ultimately one should evaluate each platform …
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.
App Engine is such a good resource for our team both internally and externally. You have complete control over your app, how it runs, when it runs, and more while Google handles the back-end, scaling, orchestration, and so on. If you are serving a tool, system, or web page, it's perfect. If you are serving something back-end, like an automation or ETL workflow, you should be a little considerate or careful with how you are structuring that job. For instance, the Standard environment in Google App Engine will present you with a resource limit for your server calls. If your operations are known to take longer than, say, 10 minutes or so, you may be better off moving to the Flexible environment (which may be a little more expensive but certainly a little more powerful and a little less limited) or even moving that workflow to something like Google Compute Engine or another managed service.
Obviously, for any business, there are two main areas to focus on — the sales path and the service path. Sales Cloud wouldn’t be suited for a company that’s primarily into support services. For those kinds of companies, Salesforce has a different product — Service Cloud. So, for anyone in the support or service space, Sales Cloud isn’t the right fit.
The customizations - We have an organization that operates differently from most companies, so we’ve had to implement quite a few customizations — and Salesforce allows us to do that quite quickly. Most of the time, delays come from dependencies on other internal parties rather than the system itself.
From my perspective as a consultant, one of the biggest advantages is that everything is in Salesforce — all the details, all in one place. The ability to customize it easily is a big plus; there’s really a lot you can do with it.
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.
There is a slight learning curve to getting used to code on Google App Engine.
Google Cloud Datastore is Google's NoSQL database in the cloud that your applications can use. NoSQL databases, by design, cannot give handle complex queries on the data. This means that sometimes you need to think carefully about your data structures - so that you can get the results you need in your code.
Setting up billing is a little annoying. It does not seem to save billing information to your account so you can re-use the same information across different Cloud projects. Each project requires you to re-enter all your billing information (if required)
We still need to include the production part. We started using Salesforce to sell the seeds — our inventory is in SAP — and from there we handle sales and track the process of planting, harvesting, selling, and then collecting payments. But we don’t yet manage the earlier production processes, like production planning. We handle allocation, but not full production planning, and that’s an area where we still have room for improvement.
App Engine is a solid choice for deployments to Google Cloud Platform that do not want to move entirely to a Kubernetes-based container architecture using a different Google product. For rapid prototyping of new applications and fairly straightforward web application deployments, we'll continue to leverage the capabilities that App Engine affords us.
There are days when I wish we hadn't switched, but I know that if we put in the time, we will get to where we want to be with the software and that it has many more capabilities than anything else we looked at. However, the amount of time and onboarding we need to do is also far greater than we realized/were told when we originally bought the product. They told us we should hire onboarding support, but at the end, after we had already reached our budget maximum for this, so it's been slower than we had hoped.
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.
I had to revisit the UI after a year of just setting up and forgetting. The UI got some improvements but the amount of navigation we have to go through to setup a new app has increased but also got easier to setup. Gemini now is integrated and make getting answers faster
Because I think it could be easier. We have different standards today since we’re used to interacting with consumer apps like Starbucks, where all you do is scan your card. Then, when you use Sales Cloud, there are still a lot of manual inputs. So my mission with AI is really about figuring out how to make that easier.
Salesforce is always available securely from any internet-capable device anywhere in the world, UNLESS you choose to set security measures so that ONLY trusted IP ranges may access the system at certain times of the day. It's all about choice and flexibility with Salesforce products.
Salesforce performance in general is excellent. "The cloud infrastructure beneath Force.com has been fine-tuned over the past 10 years. It powers nearly 100,000+ businesses running more than 185,000 applications that 3 million users count on every day." Points per Salesforce - 1) Multitenant kernel - With a multitenant platform, each business that uses the app doesn’t have its own copy. Instead, all businesses share a single copy and then customize it for their specific needs. 2) ISO 27001 certified security - You can’t compromise when it comes to enterprise-level security. Force.com is road-tested and trusted by nearly 100,000+ companies, including many of the world’s most security-conscious organizations, such as banks and health care providers. 3) Proven reliability - All Force.com apps run on world-class data centers with backup, failover, and disaster-recovery facilities. Force.com has had a proven 99.9 percent uptime record for years. 4) Proven, real-time scalability - Force.com is used by many of the world's largest enterprises, including Cisco, Japan Post Network, and Symantec. Applications can automatically scale from a few users to millions of page views, as needed. 5) Real-time query optimizer - You need fast access to your data. The Force.com query optimizer delivers under 300ms response time, at a massive scale. 6) Real-time transparent system status - You can always see real-time system performance, availability, and security information at trust.salesforce.com. 7) Real-time upgrades - Unlike traditional software platforms, our upgrades never break your customizations, code, or integrations. We upgrade the platform for you 3 to 4 times each year. As a result, you’re always on the latest version, with access to the latest features, performance, and security enhancements. 8) Real-time sandbox environments - With a single click, you can create copies of your applications, configuration, and data in separate environments for development, testing, and training. 9) Three global production data centers and disaster recovery - Force.com runs on three geographically dispersed, mirrored data centers with built-in replication, disaster recovery, a redundant network backbone, and no single points of failure
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.
Good amount of documentation available for Google App Engine and in general there is large developer community around Google App Engine and other products it interacts with. Lastly, Google support is great in general. No issues so far with them.
The overall support has been good. More and more features are being released quite frequently. Very small features are also making big difference in how the tool can be adapted and used better. If there is anything we need or are stuck, the support team sets up a call and helps in resolving the issue/provides workarounds.
I attended two training sessions. I would rate them a 4 as an advanced user. It was very basic – great for someone new – would give 8+ for new person.
I had 3 years of experience at the time. I skipped basic and went onto advanced and still not helpful. A lot of it was best practices that didn’t feel relevant for our business
I have gone through multiple. The content that’s delivered is quite basic – I wish they had more advanced training.
We are grandfathered into premium support plus training. We get unlimited access to instructor led and online training for free. We have taken advantage of this
Just from an organizational standpoint - we standardized our data prior to moving to Salesforce. But we essentially standardized it wrong. That's created a big disgusting mess for us know that I'll have to deal with as the Admin. Be sure you think through use cases prior to doing something like that - seek outside opinions on how the data will work best, especially depending on what else you're going to integrate with Salesforce.
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 on another much smaller cloud provider and decided to make the switch for several reasons - stability, breadth of services, and security. In reviewing options, GCP provided the best mixtures of meeting our needs while also balancing the overall cost of the service as compared to the other major players in Azure and AWS.
So I've evaluated, implemented Microsoft Dynamics in the past. I've used Oracle CRM solutions. I've used Daylight, which is a very niche CRM system the last couple of years. And I've evaluated a variety from Legacy Microsoft Ones to Zoho and Sugar when making implementation decisions at other companies. But usually I've gone with Salesforce. I'd say it's better than most. The only one that I generally prefer, and last time I chose an implementation from scratch, I did Microsoft Dynamics. And the reason is for small mid-size organization, Microsoft Dynamics, if you already have Microsoft Office products, it's much better integrated to all of the Excel, Word, OneNote, Outlook email than what you get from Salesforce. And so that's the only one that if someone's a Microsoft organization and small sized company, it'll save a lot of integration things, a lot of security, a lot of login and access and IT management by just sticking within the Microsoft ecosystem. But outside of that, if you don't use Microsoft or if you're a large organization or have other needs that you want, Salesforce I'd say is better than all of the other CRM offerings out there. It's the easiest to use and the most robust and the most vendors and products for the ecosystem.
Salesforce is the most widely used CRM system. Professionalism tends to increase when things go wrong for market leaders. Salesforce considers us as users because they own the market. Having all of our data in one place and all of our teams working within Salesforce. Anyone who uses Salesforce is impacted by it, even if they don't.
It's very scalable as it has a ton of features (but you do need an admin who understands how to leverage these features). Because of the various features, we've also needed to host onboarding sessions with our users so that they can familiarize themselves with the platform, which isn't always super user-friendly or intuitive.
Using Salesforce.com has made my daily routines more efficient and simplified the manual tasks I had to perform independently. I can now access data from any device, online or offline, and provide better guidance to my team about the forecasts provided by the built-in artificial intelligence (AI). A chat with a Salesforce support specialist would be great. The knowledge base has a community forum where Salesforce users can ask questions and learn more about the product.
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.
Effective integration to other java based frameworks.
Time to market is very quick. Build, test, deploy and use.
The GAE Whitelist for java is an important resource to know what works and what does not. So use it. It would also be nice for Google to expand on items that are allowed on GAE platform.
It allows me to keep a close eye on all of my performance metrics through the Dashboard Reporting, ie what my sales pipeline looks like, how much it's changed in the last 60 days, new opportunities created in the last 7 days, # of emails sent for the week, etc. The ease of the design and output make it really easy to check my progress throughout the day to find where I have holes and am falling short on my personal and work goals. It's resulted in greater transparency with my Mgmt Team and shorter 1-on-1 mtgs with my boss as he can see exactly where I am at all times (to be fair, I'm a senior sales rep, so he pretty much lets me do my job completely unfettered), but it does prove that I am continually producing which recently resulted in a raise I didn't even ask for.
The SF repository is so detailed that I don't have to spend tons of time finding frequently used websites attached to a client or see what all interactions with the company look like. Even though I don't use SF for my bulk emails and email sequences, SF provides me with an email to use in the bcc of these emails which links everything back to SF. I find that extremely helpful. This really impacts my efficiency and I can honestly say that once I started using all the functionality of data management, it saved me about 20% of my time/week that I could then allocate towards other revenue-generating tasks like prospecting and account management. The more time I have for those, the better. My year-over-year on accounts 1 year and older just grew by 17% this last year.
