Apache Hadoop vs. Google App Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 7.5 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
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
Apache HadoopGoogle App Engine
Editions & Modules
No answers on this topic
Starting Price
$0.05
Per Hour Per Instance
Max Price
$0.30
Per Hour Per Instance
Offerings
Pricing Offerings
HadoopGoogle App Engine
Free Trial
NoNo
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HadoopGoogle App Engine
Features
Apache HadoopGoogle App Engine
Platform-as-a-Service
Comparison of Platform-as-a-Service features of Product A and Product B
Apache Hadoop
-
Ratings
Google App Engine
9.5
32 Ratings
20% above category average
Ease of building user interfaces00 Ratings9.018 Ratings
Scalability00 Ratings10.032 Ratings
Platform management overhead00 Ratings9.032 Ratings
Workflow engine capability00 Ratings8.024 Ratings
Platform access control00 Ratings10.031 Ratings
Services-enabled integration00 Ratings10.028 Ratings
Development environment creation00 Ratings10.029 Ratings
Development environment replication00 Ratings10.028 Ratings
Issue monitoring and notification00 Ratings9.028 Ratings
Issue recovery00 Ratings9.026 Ratings
Upgrades and platform fixes00 Ratings10.029 Ratings
Best Alternatives
Apache HadoopGoogle App Engine
Small Businesses

No answers on this topic

AWS Lambda
AWS Lambda
Score 8.3 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Red Hat OpenShift
Red Hat OpenShift
Score 9.2 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.2 out of 10
Red Hat OpenShift
Red Hat OpenShift
Score 9.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HadoopGoogle App Engine
Likelihood to Recommend
8.0
(37 ratings)
8.0
(35 ratings)
Likelihood to Renew
9.6
(8 ratings)
8.3
(8 ratings)
Usability
8.0
(6 ratings)
7.7
(7 ratings)
Performance
8.0
(1 ratings)
10.0
(1 ratings)
Support Rating
7.5
(3 ratings)
8.4
(12 ratings)
Online Training
6.1
(2 ratings)
-
(0 ratings)
Implementation Rating
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
Apache HadoopGoogle App Engine
Likelihood to Recommend
Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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Google
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.
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Pros
Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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Google
  • Quick to develop, quick to deploy. You can be up and running on Google App Engine in no time.
  • Flexible. We use Java for some services and Node.js for others.
  • Great security features. We have been consistently impressed with the security and authentication features of Google App Engine.
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Cons
Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
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Google
  • 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)
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Likelihood to Renew
Apache
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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Google
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.
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Usability
Apache
As Hadoop enterprise licensed version is quite fine tuned and easy to use makes it good choice for Hadoop administrators. It’s scalability and integration with Kerberos is good option for authentication and authorisation. installation can be improved. logging can be improved so that it become easier for debugging purposes. parallel processing of data is achieved easily.
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Google
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
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Support Rating
Apache
It's a great value for what you pay, and most Data Base Administrators (DBAs) can walk in and use it without substantial training. I tend to dabble on the analyst side, so querying the data I need feels like it can take forever, especially on higher traffic days like Monday.
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Google
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.
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Online Training
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Google
No answers on this topic
Alternatives Considered
Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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Google
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.
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Return on Investment
Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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Google
  • Effective employee adoption through ease of use.
  • 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.
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ScreenShots