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28 Ratings
230 Ratings
28 Ratings
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Score 8.2 out of 101
230 Ratings
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Score 8.3 out of 101

Likelihood to Recommend

Amazon EMR

Amazon Elastic MapReduce is useful in cases where two conditions are met. First, that you are planning on using multiple big data tools simultaneously to analyze big data sets. And second, that you need a tool that simplifies managing big data tools. If these two conditions are met, MapReduce does a great job. The user interface is simple. The program eliminates some programming requirements. The software also makes setting up big data analyses much easier. With these benefits acknowledged, MapReduce is not a good tool for "small" data analyses, given that there are other tools that do the job quicker and much more professional output. If you're on the fence, try out MapReduce with competing "small" data tools and see if you really need big data software.
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Hadoop

Hadoop is well suited for healthcare organizations that deal with huge amounts of data and optimizing data.
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Pros

Amazon EMR

  • EMR does well in managing the cost as it uses the task node cores to process the data and these instances are cheaper when the data is stored on s3. It is really cost efficient. No need to maintain any libraries to connect to AWS resources.
  • EMR is highly available, secure and easy to launch. No much hassle in launching the cluster (Simple and easy).
  • EMR manages the big data frameworks which the developer need not worry (no need to maintain the memory and framework settings) about the framework settings. It's all setup on launch time. The bootstrapping feature is great.
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Hadoop

  • Hadoop is a very cost effective storage solution for businesses’ exploding data sets.
  • Hadoop can store and distribute very large data sets across hundreds of servers that operate, therefore it is a highly scalable storage platform.
  • Hadoop can process terabytes of data in minutes and faster as compared to other data processors.
  • Hadoop File System can store all types of data, structured and unstructured, in nodes across many servers
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Cons

Amazon EMR

  • The analytical processes generally run quicker with the standalone tools of Hadoop, Spark, and others. If you only use one big data tool and don't really need things simplified, then Elastic MapReduce is more of an overhead tool that doesn't add much value.
  • The analytical capabilities of Elastic MapReduce are nowhere near as complex or broad as non-big data tools. I would suggest not using the tool unless your data really is big data.
  • The machine learning capabilities of Elastic MapReduce (using the big data tools of Hadoop/Spark) are good but are not as easy to use as other machine learning tools.
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Hadoop

  • Hadoop is a batch oriented processing framework, it lacks real time or stream processing.
  • Hadoop's HDFS file system is not a POSIX compliant file system and does not work well with small files, especially smaller than the default block size.
  • Hadoop cannot be used for running interactive jobs or analytics.
Mrugen Deshmukh profile photo

Likelihood to Renew

Amazon EMR

No score
No answers yet
No answers on this topic

Hadoop

Hadoop 9.6
Based on 8 answers
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
Bhushan Lakhe profile photo

Usability

Amazon EMR

No score
No answers yet
No answers on this topic

Hadoop

Hadoop 9.0
Based on 3 answers
I found it really useful during my academic projects. Data handling for large data sets was easy with Hadoop. It used to work really fast for bigger data sets. I found it reliable.
Tushar Kulkarni profile photo

Online Training

Amazon EMR

No score
No answers yet
No answers on this topic

Hadoop

Hadoop 6.1
Based on 2 answers
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Alternatives Considered

Amazon EMR

Having one of these enterprise edition license comes at its own costs. But, the flexibility to have the cluster spin up with the workbenches and code snippets on the same is really beneficial. Especially, if one had to move out of EMR and consider an option which reduces the debugging time in establishing connections to AWS resources, I would love to used the mentioned three resources on EC2. This would definitely make the processing time to reduce as there is a flexibility to test real time and execute the code snippet and look at the performance and monitor the snippet in real time.
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Hadoop

Apache Spark has an in memory processing model, making it powerful for lightning fast data processing. Apache Spark also exposes Scala and Python in APIs which is one of the most commonly used programming languages in data analytic and data processing domains.
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Return on Investment

Amazon EMR

  • It was obviously cheaper and convenient to use as most of our data processing and pipelines are on AWS. It was fast and readily available with a click and that saved a ton of time rather than having to figure out the down time of the cluster if its on premises.
  • It saved time on processing chunks of big data which had to be processed in short period with minimal costs. EMR solved this as the cluster setup time and processing was simple, easy, cheap and fast.
  • It had a negative impact as it was very difficult in submitting the test jobs as it lags a UI to submit spark code snippets.
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Hadoop

  • MapReduce jobs run way faster when compared to traditional batch processing jobs resulting in getting better value of data
  • Since Hadoop is free , lots of cost savings
  • Since it is distributed, no fear of data failures
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Pricing Details

Amazon EMR

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Hadoop

General

Free Trial
Free/Freemium Version
Yes
Premium Consulting/Integration Services
Entry-level set up fee?
No

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