Amazon Web Services (AWS) is a subsidiary of Amazon that provides on-demand cloud computing services. With over 165 services offered, AWS services can provide users with a comprehensive suite of infrastructure and computing building blocks and tools.
$100
per month
Hadoop
Score 7.4 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.
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Pricing
Amazon Web Services
Apache Hadoop
Editions & Modules
Free Tier
$0
per month
Basic Environment
$100 - $200
per month
Intermediate Environment
$250 - $600
per month
Advanced Environment
$600-$2500
per month
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Offerings
Pricing Offerings
Amazon Web Services
Hadoop
Free Trial
Yes
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
AWS allows a “save when you commit” option that offers lower prices when you sign up for a 1- or 3- year term that includes an AWS service or category of services.
AWS has more APIs to use on the cloud. Microsoft has an API mainly for the Microsoft platform. And Google has different big data analytics than other competitors [do].
Hadoop utilizes a SQL structure, which is great. You pay less for the services, but it's definitely less of an enterprise-level option and more just a good place to store your seldom-used data. Teradata and AWS are a lot faster in returning queries than Hadoop, but you pay …
Processing of big data has been the ultimate need for the me choosing Hadoop. Big data is massive and messy, and it’s coming at you uncontrolled. Data are gathered to be analyzed to discover patterns and correlations that could not be initially apparent, but might be useful in …
One of the scenarios I can think of is to Deploy a web application that may experience fluctuating traffic. AWS EC2 and Elastic Beanstalk allow for quick deployment and easy scaling accommodating traffic spikes without downtime. Next thing is to analyze large datasets for business insights. AWS services like EMR (Elastic MapReduce) and Redshift enable efficient processing and analysis of big data with minimal setup. Now for one of the scenarios where is less appropriate is if we want to host a simple static website, for basic sites using a dedicated hosting service like GitHub Pages or Netlify may be simpler and most effective than AWS
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.
If there is one thing I think AWS needs improvement on, it is the administration dashboard. It can be a nightmare to use especially when trying to access billing. This could be made better, honestly, as there should be a simplified way to access simple admin features.
While AWS was fairly easy to integrate into our solutions, it is not as easy to use without some IT knowledge. The dashboards are complicated and designed for someone who is computer savvy. If you are just want to keep track of billing, for example, you may need to take a course or spend a few hours with someone being walked through the admin console.
AWS does tend to be slow at times. If you do not have a fast internet connection, it can take time to access services that are hosted on AWS. This is not always the case but we have had clients complain about this if they are trying to access a service from multiple points (IP addresses). The only real fix we found was to make our files cache to another server and only keep current data accessible to clients.
We are almost entirely satisfied with the service. In order to move off it, we'd have to build for ourselves many of the services that AWS provides and the cost would be prohibitive. Although there are cost savings and security benefits to returning to the colo facility, we could never afford to do it, and we'd hate to give up the innovation and constant cycle of new features that AWS gives us.
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
Amazon Web Services is a great tool when it comes to middle size organizations like us. It provides multiple tools and functionalities in low costs. The best feature we have to pay as we go. No financial burden on company for the unused instances. It also comes with greater level of security such as two level authorization such as multi factor authorization.
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.
AWS does not provide the raw performance that you can get by building your own custom infrastructure. However, it is often the case that the benefits of specialized, high-performance hardware do not necessarily outweigh the significant extra cost and risk. Performance as perceived by the user is very different from raw throughput.
The customer support of Amazon Web Services are quick in their responses. I appreciate its entire team, which works amazingly, and provides professional support. AWS is a great tool, indeed, to provide customers a suitable way to immediately search for their compatible software's and also to guide them in a good direction. Moreover, this product is a good suggestion for every type of company because of its affordability and ease of use.
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.
Amazon Web Services is well suited when we have a huge amount of data to store, process, manipulate and get meaningful information out of. It is also suitable when we need very fast data retrieval from the database. They provide a superior product at a fair price which allows us to further our goals and push the limits of what we are capable of as a team / company.
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.
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.