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
UiPath Automation Platform
Score 8.5 out of 10
N/A
UiPath's agentic platform combines the company's Robotic Process Automation (RPA) solution for automating repetitive tasks with agentic automation. By unifying agentic AI, automation, BPM, and process intelligence, the platform gives organizations control to design, run, and optimize new agentic processes.
$25
per month (for 1 user with basic tier features)
Pricing
AWS Lambda
Google App Engine
UiPath Automation Platform
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
Automation Cloud Basic
$25
per month 1 user, 1 basic platform tier
Automation Cloud Enterprise
Contact Sales
Enterprise Medium Business
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Automation Cloud Standard
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Automation Cloud Basic
starting at $25
per month 1 user, 1 basic platform tier
Automation Suite
Contact Sales
Offerings
Pricing Offerings
AWS Lambda
Google App Engine
UiPath Automation Platform
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
No setup fee
Additional Details
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More Pricing Information
Community Pulse
AWS Lambda
Google App Engine
UiPath Automation Platform
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 …
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.
UiPath Automation Platform is well-suited for automating repetitive and time-consuming tasks such as invoice processing, data entry, and report generation. By using UiPath Automation Platform, employees can focus on more strategic tasks, which leads to increased efficiency. Additionally, UiPath Automation Platform is highly effective at automating rule-based processes, such as financial processes like bank statement reconciliation, account payable, and account receivable processes that follow a set of predetermined rules.
Any type of application can be automated (Desktop Application, Web Application and also applications reachable only via remote technologies such as Citrix, Remote Desktop and so on).
The writing of a process code takes place entirely through the use of objects. In the event that there were no objects capable of solving a particular problem, it is possible to use some languages of the .net platform such as: VB.net, C#.
It is easy to scale the solution by adding more robots to run a process in case the solution requires more performance in the future.
It can also be used by functional analysts to design the flow to be automated.
An academy is available online where basic and advanced courses can be taken. It is also possible to take a completely free basic certification.
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)
As I mentioned, Excel automation is not very effective, there are a number of packages to add, but there is nothing as smooth as a good macro.
Working with selectors is certainly challenging and UiPath does a good job with that, but there is room for improvement since the interface could be smarter in selecting the right attributes and warn the user if something is not properly setup.
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.
This platform has so much potential and have been garnering a lot of attention by proving benefits in terms of saving operational and manpower costs. I am sure with minute efforts we were able to achieve our ROI and the same is the case with many of our customers whom we have been working around Digital Automation initiatives.
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
There are two main reasons with this rating 1. UiPath Automation Platform requires the old school type of Change Weather management, Which actually eats a lot of time to manage and roll out the recent changes. There is not something kind of CI/CD when you are developing the things With UiPath Automation Platform. 2. Very high development and maintenance cost, which actually decrease its usability.
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.
UiPath RPA has an exceptional studio interface. It has been a year and so since I am using UiPath RPA. Whether it is some my personal task to scrape information & links from the Journal or find a specific character string from multiple PDF collection using OCR, UiPath RPA has made its roots to our technological ecosystem
Video material supported by text. The training has evolved a lot in the past 3 years to become more attractive. Specific training tracks exist for the different roles in RPA development, where everyone is expected to learn basic development.
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.
As compared to other products, we require programming knowledge and concepts to work but UiPath is for everyone. It provides us extensive event logging at various stages and effective exception handling for applications and business. It increases our agility and enhances the overall productivity further by using the source control SVC. The solution that we implemented is also very scalable in terms of incorporating new requirements.
The open source tools require lots of IT effort in order to set up and maintain over time. UiPath is like a complete package and customer service is also active in terms of solving issues arising while automating procession on a day to day basis.
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.
