Likelihood to Recommend 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.
Read full review I have been using AWS Elastic Beanstalk for more than 5 years, and it has made our life so easy and hassle-free. Here are some scenarios where it excels -
I have been using different AWS services like EC2, S3, Cloudfront, Serverless, etc. And Elastic Beanstalk makes our lives easier by tieing each service together and making the deployment a smooth process. N number of integrations with different CI/CD pipelines make this most engineer's favourite service. Scalability & Security comes with the service, which makes it the absolute perfect product for your business. Personally, I haven't found any situations where it's not appropriate for the use cases it can be used. The pricing is also very cost-effective.
Read full review Pros 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. Read full review Getting a project set up using the console or CLI is easy compared to other [computing] platforms. AWS Elastic Beanstalk supports a variety of programming languages so teams can experiment with different frameworks but still use the same compute platform for rapid prototyping. Common application architectures can be referenced as patterns during project [setup]. Multiple environments can be deployed for an application giving more flexibility for experimentation. Read full review Cons 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 Read full review Limited to the frameworks and configurations that AWS supports. There is no native way to use Elastic Beanstalk to deploy a Go application behind Nginx, for example. It's not always clear what's changed on an underlying system when AWS updates an EB stack; the new version is announced, but AWS does not say what specifically changed in the underlying configuration. This can have unintended consequences and result in additional work in order to figure out what changes were made. Read full review Likelihood to Renew 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
Read full review As our technology grows, it makes more sense to individually provision each server rather than have it done via beanstalk. There are several reasons to do so, which I cannot explain without further diving into the architecture itself, but I can tell you this. With automation, you also loose the flexibility to morph the system for your specific needs. So if you expect that in future you need more customization to your deployment process, then there is a good chance that you might try to do things individually rather than use an automation like beanstalk.
Read full review Usability Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.
Read full review It is a great tool to manage your applications. You just need to write the codes, and after that with one click, your app will be online and accessible from the internet. That is a huge help for people who do not know about infrastructure or do not want to spend money on maintaining infrastructure.
Read full review Support Rating We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.
Gene Baker Vice President, Chief Architect, Development Manager and Software Engineer
Read full review As I described earlier it has been really cost effective and really easy for fellow developers who don't want to waste weeks and weeks into learning and manually deploying stuff which basically takes month to create and go live with the Minimal viable product (MVP). With AWS Beanstalk within a week a developer can go live with the Minimal viable product easily.
Read full review Online Training Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
Read full review Implementation Rating - Do as many experiments as you can before you commit on using beanstalk or other AWS features. - Keep future state in mind. Think through what comes next, and if that is technically possible to do so. - Always factor in cost in terms of scaling. - We learned a valuable lesson when we wanted to go multi-region, because then we realized many things needs to change in code. So if you plan on using this a lot, factor multiple regions.
Read full review Alternatives Considered 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.
Read full review We also use
Heroku and it is a great platform for smaller projects and light Node.js services, but we have found that in terms of cost, the Elastic Beanstalk option is more affordable for the projects that we undertake. The fact that it sits inside of the greater AWS Cloud offering also compels us to use it, since integration is simpler. We have also evaluated
Microsoft Azure and gave up trying to get an extremely basic implementation up and running after a few days of struggling with its mediocre user interface and constant issues with documentation being outdated. The authentication model is also badly broken and trying to manage resources is a pain. One cannot compare Azure with anything that Amazon has created in the cloud space since Azure really isn't a mature platform and we are always left wanting when we have to interface with it.
Read full review Return on Investment 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. Read full review till now we had not Calculated ROI as the project is still evolving and we had to keep on changing the environment implementation it meets our purpose of quick deployment as compared to on-premises deployment till now we look good as we also controlled our expenses which increased suddenly in the middle of deployment activity Read full review ScreenShots