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 7.5 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.
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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 …
This is something that is actually common across most cloud providers. A comprehensive understanding of one's use cases, constraints and future directions is key to determining if you even need a cloud solution. If you are a 2-person startup developing something with a best-scenario audience of 1k DAU in a year, you would very likely best served by a dirt-cheap dedicated Linux server somewhere (and your options to graduate to a cloud solution will still be open). If, however, you are a bigger fish, and/or you are actively considering build-vs-buy decisions for complicated, highly-loaded, six-figure requests per minute systems, global loadbalancing, extreme growth projections - then MAYBE you solve all or part of it with a cloud provider. And depending on your taste for risk, reliability, flexibility, track record - it might be 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.
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
AWS offers a wide range of powerful services that cater to various business needs which is significant strength. The ability to scale resources on-demand is a major advantage making it suitable for businesses of all sizes. The sheer volume of options and configurations can be overwhelming for new users leading to a steep learning curve. While functional the AWS management console can feel cluttered and less intuitive compared to some competitors which can hinder navigation. Although some documentation lacks clarity and practical examples which can frustrate users trying to implement specific solutions.
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 fits best for all levels of organisations like startup, mid level or enterprise. The services are easy to use and doesn't require a high level of understanding as you can learn via blogs or youtube videos. AWS is Reasonable in cost as the plan is pay as you use.
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.
Using Amazon Web Services has allowed us to develop and deploy new SAAS solutions quicker than we did when we used traditional web hosting. This has allowed us to grow our service offerings to clients and also add more value to our existing services.
Having AWS deployed has also allowed our development team to focus on delivering high-quality software without worrying about whether our servers will be able to handle the demand. Since AWS allows you to adjust your server needs based on demand, we can easily assign a faster server instance to ease and improve service without the client even knowing what we did.
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.
