The Amazon Elastic Transcoder from AWS is a cloud-based media transcoding service available to AWS users which is priced on the volume of media transcoded by minute and the media's resolution. The service is scalable and anticipates transcoding of very large files or high volumes of files.
$0
per minute
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
Google Compute Engine
Score 8.6 out of 10
N/A
Google Compute Engine is an infrastructure-as-a-service (IaaS) product from Google Cloud. It provides virtual machines with carbon-neutral infrastructure which run on the same data centers that Google itself uses.
$0
per month GB
Pricing
Amazon Elastic Transcoder
Google App Engine
Google Compute Engine
Editions & Modules
Audio Only
$0.0045
per minute
Less than 720p
$0.015
per minute
720p and above
$0.03
per minute
Starting Price
$0.05
Per Hour Per Instance
Max Price
$0.30
Per Hour Per Instance
Preemptible Price - Predefined Memory
0.000892 / GB
Hour
Three-year commitment price - Predefined Memory
$0.001907 / GB
Hour
One-year commitment price - Predefined Memory
$0.002669 / GB
Hour
On-demand price - Predefined Memory
$0.004237 / GB
Hour
Preemptible Price - Predefined vCPUs
0.006655 / vCPU
Hour
Three-year commitment price - Predefined vCPUS
$0.014225 / CPU
Hour
One-year commitment price - Predefined vCPUS
$0.019915 / vCPU
Hour
On-demand price - Predefined vCPUS
$0.031611 / vCPU
Hour
Offerings
Pricing Offerings
Amazon Elastic Transcoder
Google App Engine
Google Compute Engine
Free Trial
Yes
No
Yes
Free/Freemium Version
Yes
Yes
Yes
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
Amazon Elastic Transcoder offers a monthly free usage tier. The free tier consists of: 20 minutes of free audio-only output per month, 20 minutes of free SD output per month and 10 minutes of free HD output per month. Once you exceed the number of minutes in this free usage tier, you will be charged at the prevailing rates.
—
Prices vary according to region (i.e US central, east, & west time zones). Google Compute Engine also offers a discounted rate for a 1 & 3 year commitment.
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 …
It's the manageability of the Google App Engine which made it a better option in our case. It's quite straightforward to deploy on App-Engine. No worries for monitoring setup
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 …
You can spawn up your own cluster using Kubernetes or Container Engine which will scale automatically when configured properly, but you have to keep an eye on that cluster. In App Engine you don't have to worry about it at all, just ship your code and it will run.
RunMyProcess is a good solution if you have a relatively straight forward workflow application. However, this solution charges for every page load of the application. If you have a large enterprise customer, these costs can quickly jump if thousands of people are accessing the …
Google App Engine is slower in comparison, and costs more than Google Compute Engine. We chose Google Compute Engine because Google App Engine was way too slow (mainly due to having to use Google Cloud Storage).
The perfect blend of setup flexibility, costing and trust of Google could be my answer to the comparison. This being a server backed service so, ruling out the functions. The Setup flexibility and speed set the GCE apart from Kubernetes. Compliance, regulation and the security …
Google App Engine is a platform as a service where everything is taken care of by Google and we just need to write the code and deploy it onto it. But we hardly have much control over the VMs and the OS offering is not much. We had a limited amount of OS version supported. …
We have used a few other cloud providers of similar services and continue to use Google Compute Engine because it fits well within our technology stack and is cost-effective while providing the service we need. It has allowed us to use and experiment with many more …
We have used Amazon in the past. GCE has come such a long way since then, we have not looked back. IAM and access are on par, cost management is slightly better on GCE. Where we have really seen improvements are the VM types (GCE allows for deep customization that does not …
App Engine is somewhat similar, but we use it together with Compute Engine. App Engine is good for serving end requests to users -- it can scale automatically to any number of requests, but has it's own limitations. Compute Engine does not have any limitations. but you have to …
It is well suited in a large setting where people use different file formats and various apps to record and transfer their audio or video files across devices. In such scenarios, the transcoder would of real help to eliminate the hassle of converting the files into desired formats for viewing or doing some other analysis.
The transcoder would not be of much use if all the files have the same format and does not need any conversion from their source file formats. It would prove costly and not useful if it's just an additional step that is of no particular use
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.
You can use Google Cloud Compute Engine as an option to configure your Gitlab, GitHub, and Azure DevOps self-hosted runners. This allows full control and management of your runners rather than using the default runners, which you cannot manage. Additionally, they can be used as a workspace, which you can provide to the employees, where they can test their workloads or use them as a local host and then deploy to the actual production-grade instance.
Scaling - whether it's traffic spikes or just steady growth, Google Compute Engine's auto-scaling makes sure we've got the compute power we need without any manual juggling acts
Load balancing - Keeping things smooth with that load balancing across multiple VMs, so our users don't have to deal with slow load times or downtime even when things get crazy busy
Customizability - Mix and match configs for CPU, RAM, storage and whatnot to suit our specific app needs
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.
Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.
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
Having interacted with several cloud services, GCE stands out to me as more usable than most. The naming and locating of features is a little more intuitive than most I've interacted with, and hinting is also quite helpful. Getting staff up to speed has proven to be overall less painful than others.
Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes
It works great all the time except for occasional issues, but overall, I am very happy with the performance. It delivers on the promise it makes and as per the SLAs provided. Networking is great with a premium network, and AZs are also widespread across geographies. Overall, it is a great infra item to have, which you can scale as you want.
Support for Amazon Elastic Transcoder is the same as any other service within AWS. If you are familiar with AWS, it is easy to start using Elastic Transcoder
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 documentation needs to be better for intermediate users - There are first steps that one can easily follow, but after that, the documentation is often spotty or not in a form where one can follow the steps and accomplish the task. Also, the documentation and the product often go out of sync, where the commands from the documentation do not work with the current version of the product.
Google support was great and their presence on site was very helpful in dealing with various issues.
Amazon Elastic Transcoder is in a league of its own when compared to other alternatives in the market. The most noticeable competitor would be either Microsoft or Adobe or Google. When I had a chance to compare Azure products and Amazon products, the difference is obvious and the experience provided by both the products are very different in terms of user experience and interaction with the application. The cost and availability also were taken into consideration when choosing between the two shortlisted choices. So we went with Amazon's product as it is widely used and has support and maintenance which is basically better than the competition.
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.
Google Compute Engine provides a one stop solution for all the complex features and the UI is better than Amazon's EC2 and Azure Machine Learning for ease of usability. It's always good to have an eco-system of products from Google as it's one of the most used search engine and IoT services provider, which helps with ease of integration and updates in the future.
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.