Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. Users can launch instances with a variety of OSs, load them with custom application environments, manage network access permissions, and run images on multiple systems.
$0.01
per IP address with a running instance per hour on a pro rata basis
AWS Lambda
Score 8.3 out of 10
N/A
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
Pricing
Amazon Elastic Compute Cloud (EC2)
AWS Lambda
Google App Engine
Editions & Modules
Data Transfer
$0.00 - $0.09
per GB
On-Demand
$0.0042 - $6.528
per Hour
EBS-Optimized Instances
$0.005
per IP address with a running instance per hour on a pro rata basis
Carrier IP Addresses
$0.005 - $0.10
T4g Instances
$0.04
per vCPU-Hour Linux, RHEL, & SLES
T2, T3 Instances
$0.05 ($0.096)
per vCPU-Hour Linux, RHEL, & SLES (Windows)
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
Offerings
Pricing Offerings
Amazon Elastic Compute Cloud (EC2)
AWS Lambda
Google App Engine
Free Trial
No
No
No
Free/Freemium Version
No
No
Yes
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
Amazon Elastic Compute Cloud (EC2)
AWS Lambda
Google App Engine
Considered Multiple Products
Amazon Elastic Compute Cloud (EC2)
Verified User
C-Level Executive
Chose Amazon Elastic Compute Cloud (EC2)
We were looking to another AWS structure which would help us to avoid a lot of low level data analysis. In fact it appears to us that if even though AWS Lambda allows a lot of really good integration with a data scientist module, our team in order to make sure we are in full …
Amazon EC2 is super flexible compared to the PaaS offerings like Heroku Platform and Google App Engine since with Amazon EC2, we have access to the terminal. In terms of pricing, it's basically just the same as Google Compute Engine. The deciding factor is Amazon EC2's native …
Verified User
Director
Chose Amazon Elastic Compute Cloud (EC2)
We chose Amazon Elastic Compute Cloud (EC2) for our Splunk workloads so that we can take advantage of directly attached high speed storage, along with the other benefits of running on Amazon Elastic Compute Cloud (EC2) instances, such as load balancing, spot pricing and general …
Amazon's been leading the way in the past few years in cloud computing and have easily become a name we can trust. When we looked at options, nothing compared to EC2 when you looked at the scalability and flexibility of the product. For the needs we were trying to meet, these …
EC2 is a much more advantageous compared with the competitors because it has a much better console, configuration, auto-scalability, uptime, and many other features that are way better than other services I have seen so far. It also provides great backup services integrated …
I have used DigitalOcean and Google Compute Engine on a trial period. EC2 was the best choice for my team due to the level of features it offers plus the ability to integrate it quickly given that we were already using so many other AWS Microservices. Getting up and running …
Security and cost are the major components which impact end users. We evaluated all the cloud platforms, and found AWS EC2 to be very cheap and more secure than GCP. Due to the improper configuration in AWS, we were compromised several times, then fixed it via some partners. …
Azure VM and Google Compute Engine are alternatives to EC2. AWS EC2 is most matures and advanced of the 3. All these provide easy-to-deploy and automatically configured third-party applications, including single virtual machine or multiple virtual machine solutions.
We chose EC2 over Azure because our tech stack was already invested in AWS. Documentation is better, and there is more community support for AWS services. EC2 is the pioneer in virtualization and we wanted to go with the stability of AWS. As far as pricing goes, EC2 can be …
AWS is by far the most mature platform, but others are catching up. We will be keeping a close eye on the competition and using them whenever they're a better fit for the workload than AWS.
It is better than other products in terms of their support team, documentation and initially, you can set up your services almost without paying anything. Apart from them, AWS services do have the best availability in any region in compared to other cloud products available …
If you want to scale your product very far, AWS is the tool to use – no doubt. It takes a lot longer to use than other products and is not trivial to use, but I have confidence my products can scale to meet the demands of millions of people with AWS. I do not have the same …
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 …
It's fine, it works as the others would have, except EC2. We are migrating back to EC2 for dedicated compute because we have scaled to a point where we have consistent traffic. The tradeoff of maintaining infrastructure in-house outweighs the benefits of moving quickly through …
We use AWS as our primary cloud provider due to the overall availability of services, AWS Lambda is just one of the services we use with AWS which allows a more seamless integration for our microservices. AWS Lambda gives us much more flexibility and can be invoked by more …
AWS Lambda is much easier to use than the near alternatives. It is so straightforward and lightweight it is my primary service for handling small transactions or triggers. The other services require more setup time and are more complex to use. AWS Lambda takes your code snippet …
When we use Lambda, we do not need to worry about the infrastructure and costs. AWS can handle it all on its own. For an optimum use case, one can always use AWS Lambda along with API Gateway and Route 53 for the best use case. Cloudwatch can help you identify any issues and …
Each service has its purpose. With EC2 you can provision servers for customers and internal projects. With EBs you can optimize what you need in performance with what you can afford. With AWS Lambda you can integrate several of these tools to work together or acomplish …
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 …
App Engine is a much more streamlined system than EC2. There is a fundamental difference between them, but they are used for basically the same thing as far a I could tell -- to serve applications EC2 is certainly more complicated, but if offers more machine-level control if …
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 …
We chose Google App Engine because it supplies the most infrastructure per dollar spent. It's much more expensive to use Amazon EC2 to scale to over a million users. Also, the engine's narrow language support system, while somewhat limiting, makes getting started quickly much …
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 …
The immediate benefits of Google App Engine is that it is essentially maintenance free as it relates to infrastructure (scalable web server and database administration). Google App Engine is more tailored to those developers that only want to focus on their applications and not …
Suitable for companies that are looking for performance at a competitive price, flexibility to switch instance type even with RI, flexibility to add-on IOPS, option to lower running cost with the regular introduction of new instance type that comes with higher performance but at a lower cost.
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.
The choices on AMIs, instance types and additional configuration can be overwhelming for any non-DevOps person.
The pricing information should be more clear (than only providing the hourly cost) when launching the instance. AWS DynamoDB gives an estimated monthly cost when creating tables, and I would love to see similar cost estimation showing on EC2 instances individually, as not all developers gets access to the actual bills.
The term for reserving instances are at least 12 months. With instance types changing so fast and better instances coming out every other day, it's really hard to commit to an existing instance type for 1 or more years at a time.
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)
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.
You an start using EC2 instances immediately, is so easy and intuitive to start using them, EC2 has wizard to create the EC2 instances in the web browser or if you are code savvy you can create them with simple line in the CLI or using an SDK. Once you are comfortable using EC2, you can even automate the process.
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
AWS's support is good overall. Not outstanding, but better than average. We have had very little reason to engage with AWS support but in our limited experience, the staff has been knowledgeable, timely and helpful. The only negative is actually initiating a service request can be a bit of a pain.
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.
Amazon EC2 is super flexible compared to the PaaS offerings like Heroku Platform and Google App Engine since with Amazon EC2, we have access to the terminal. In terms of pricing, it's basically just the same as Google Compute Engine. The deciding factor is Amazon EC2's native integration with other AWS services since they're all in the same cloud platform.
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.
It reduced the need for heavy on-premises instances. Also, it completely eliminates maintenance of the machine. Their SLA criteria are also matching business needs. Overall IAAS is the best option when information is not so crucial to post on the cloud.
It makes both horizontal and vertical scaling really easy. This keeps your infrastructure up and running even while you are increasing the capacity or facing more traffic. This leads to having better customer satisfaction.
If you do not choose your instance type suitable for your business, it may incur lots of extra costs.
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.