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.
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Heroku Platform
Score 8.2 out of 10
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The Heroku Platform, now from Salesforce, is a platform-as-a-service based on
a managed container system, with integrated data services and ecosystem for deploying modern apps. It takes an app-centric
approach for software delivery, integrated with developer tools and
workflows. It’s three main tool are: Heroku Developer Experience (DX), Heroku
Operational Experience (OpEx), and Heroku Runtime.
Heroku Developer Experience (DX)
Developers deploy directly from tools like…
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.
Heroku is very well suited for startups looking to get a server stack up and running quickly. There is little to no overhead when managing your instances. However, you'll need a background in basic DevOps or system management to make sure everything is set up correctly. In addition, it's easy to accidentally go crazy on pricing. Make sure you're only creating the server instances you need to run the base application and set up an auto-scaler plugin to handle peaks.
Heroku has a very simple deployment model, making it easy to get your application up-and-running with minimal effort. We can focus on our efforts the unique aspects of our application.
The robust add-on marketplace makes it easy to try out new approaches with minimal effort and investment -- and when we settle on a solution, we can easily scale it.
Heroku's support is quite good -- their staff is quite technical and willing to get into the weeds to diagnose even complicated problems.
Large price jumps between certain resource tiers (2x Dyno for $50 per month versus Performance Dyno for $250). Free Postgres next jumps to $50 per month.
Marketing/Branding to non-technical stakeholders. As the years pass, I've had to fight more to convince stakeholders on the value of Heroku over AWS.
Improve Buildpack documentation. This is one area where Heroku's documentation is fairly confusing.
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
Heroku is easy to use, services a ton of functions for you out of the box, and provides a means to get a software product off the ground and managed quickly and easily. The tools provide allows a small to medium size org to move very quickly. The CLI tools provided make managing an entire technical infrastructure simple.
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.
Easy to use web based console and easy to use command line tools; deployment is done directly from a GIT repository. What more could you ask for? The one thing that keeps me from giving it a 10 is that custom build packs are almost incomprehensible. We used one for a while because we needed cairo graphics processing. Fortunately, I was able to figure out a different way to do what we needed so that we could get off the custom build pack.
Heroku availability correlates pretty strongly to AWS US EAST availability. We had a couple of times where there was a Heroku-specific issue but not for the last 7-8 months.
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.
I've used it for many years without facing any major problem. It's not hard at all to get used to it, it's documentation is outstanding and simple. We are close to 2020 and I don't think most of the existing companies or startups should still face old problems such as wasting time deploying code and calculate computing resources.
Be ready to pay a bit more than expected in the beginning if you're migrating from a big server. The application is probably not ready for the change and you have to keep improving it with time.
It's also important to consider that you can't save anything to the disc as it will be lost when your application restarts, so you have to think about using something like S3.
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.
Heroku is the more expensive option for hosting compared to some of the cloud platforms we investigated, but it's worth it for us because of the plug-and-play nature of Heroku deployment. We can be up and running in a few minutes and know with precision how much it will cost us each month to run the application, unlike Amazon Web Services where you have to go to great pains to configure it correctly or else you might end up with a shocking monthly bill. Overall, spending the time to configure Amazon Web Services or one of its competitors is likely the more affordable and powerful choice, because you have control over so many specifics of the configuration. But it also requires the burden of continuing to maintain and update your AWS instance, whereas with Heroku they take care of security fixes and platform upgrades. It's a great service and we are happy to pay the extra cost for the value-adds Heroku provides.
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.
