Amazon EMR (Elastic MapReduce) vs. Cloudera Enterprise Data Hub

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon EMR
Score 8.6 out of 10
N/A
Amazon EMR is a cloud-native big data platform for processing vast amounts of data quickly, at scale. Using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi (Incubating), and Presto, coupled with the scalability of Amazon EC2 and scalable storage of Amazon S3, EMR gives analytical teams the engines and elasticity to run Petabyte-scale analysis.N/A
Cloudera Enterprise Data Hub
Score 9.0 out of 10
N/A
The Cloudera Enterprise Data Hub powered by SDX is a multifunction analytics solution that supports a range of operational and analytic use cases for enterprises.N/A
Pricing
Amazon EMR (Elastic MapReduce)Cloudera Enterprise Data Hub
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon EMRCloudera Enterprise Data Hub
Free Trial
NoNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Amazon EMR (Elastic MapReduce)Cloudera Enterprise Data Hub
Considered Both Products
Amazon EMR
Chose Amazon EMR (Elastic MapReduce)
The alternatives to EMR are mainly hadoop distributions owned by the 3 companies above. I have not used the other distributions so it is difficult to comment, but the general tradeoff is, at the cost of a longer setup time and more infra management, you get more flexible …
Chose Amazon EMR (Elastic MapReduce)
EMR provides dynamic cluster size, lots of documentation, and integration with other Amazon Web Services which are some of the things that Cloudera distribution for Hadoop lacked. Some products are hard to learn but EMR was much easier and helped save time spent on trying to …
Cloudera Enterprise Data Hub

No answer on this topic

Top Pros
Top Cons
Best Alternatives
Amazon EMR (Elastic MapReduce)Cloudera Enterprise Data Hub
Small Businesses

No answers on this topic

Google BigQuery
Google BigQuery
Score 8.6 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Snowflake
Snowflake
Score 9.0 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
Oracle Exadata
Oracle Exadata
Score 8.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon EMR (Elastic MapReduce)Cloudera Enterprise Data Hub
Likelihood to Recommend
8.4
(18 ratings)
9.0
(12 ratings)
Likelihood to Renew
-
(0 ratings)
8.2
(7 ratings)
Usability
8.3
(3 ratings)
-
(0 ratings)
Support Rating
9.0
(3 ratings)
-
(0 ratings)
User Testimonials
Amazon EMR (Elastic MapReduce)Cloudera Enterprise Data Hub
Likelihood to Recommend
Amazon AWS
We are running it to perform preparation which takes a few hours on EC2 to be running on a spark-based EMR cluster to total the preparation inside minutes rather than a few hours. Ease of utilization and capacity to select from either Hadoop or spark. Processing time diminishes from 5-8 hours to 25-30 minutes compared with the Ec2 occurrence and more in a few cases.
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Cloudera
Cloudera excels at seamless migrations and upgrades.



Cloudera supports self-healing and data center
replacement of failed cloud instances while maintaining the state.



Cloudera is essential to increase or decrease
capacity through the user interface or API.



Cloudera is great at simplifying big data analytics
by providing the technology and tools needed to gain insights from IoT and
connected devices to help monitor and condition our assets.



Cloudera's cybersecurity platform option offers
stronger anomaly detection, visibility, and prevention, as well as faster
behavioral analysis.



Cloudera is beneficial for enabling and utilizing
the platform's machine learning and ad-hoc queries while securely storing,
retrieving, and analyzing any volume of data at scale.
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Pros
Amazon AWS
  • 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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Cloudera
  • Excellent management capabilities via Cloudera Manager.
  • Open source and does not restrict our data to be bound by a proprietary format.
  • Offers excellent support for data governance and auditing.
  • Has all the components that would help us build a data hub.
  • Excellent platform support offered by Cloudera.
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Cons
Amazon AWS
  • It would have been better if packages like HBase and Flume were available with Amazon EMR. This would make the product even more helpful in some cases.
  • Products like Cloudera provide the options to move the whole deployment into a dedicated server and use it at our discretion. This would have been a good option if available with EMR.
  • If EMR gave the option to be used with any choice of cloud provider, it would have helped instead of having to move the data from another cloud service to S3.
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Cloudera
  • Not fully Open Source, couple of components of the distributions are privately owned, meaning with public contributions are not welcome
  • Improvements to Cloudera manager can only be recommended. its very hard to get it done once recommended as the full control is with them.
  • Should make components more aligned to Open Source rather than making it closed sourced.
  • Custom Features of open source software tools supported only by Cloudera are tricky. Cant commit changes to tools like Hue.
  • Improvements to Cluster Management tool is required, which are already available to its competitors.
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Likelihood to Renew
Amazon AWS
No answers on this topic
Cloudera
Likely to renew the use in case the requirements for Cloudera remain valid. The rapid change in customer requirements and solutions that must be validated, integrated or tested changes. As the maturity of the solution increases, the requirements to renew use decrease. From a solution feature perspective by itself would probably grade 10.
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Usability
Amazon AWS
I give Amazon EMR this rating because while it is great at simplifying running big data frameworks, providing the Amazon EMR highlights, product details, and pricing information, and analyzing vast amounts of data, it can be run slow, freeze and glitch sometimes. So overall Amazon EMR is pretty good to use other than some basic issues.
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Cloudera
No answers on this topic
Support Rating
Amazon AWS
There's a vast group of trained and certified (by AWS) professionals ready to work for anyone that needs to implement, configure or fix EMR. There's also a great amount of documentation that is accessible to anyone who's trying to learn this. And there's also always the help of AWS itself. They have people ready to help you analyze your needs and then make a recommendation.
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Cloudera
No answers on this topic
Alternatives Considered
Amazon AWS
Snowflake is a lot easier to get started with than the other options. Snowflake's data lake building capabilities are far more powerful. Although Amazon EMR isn't our first pick, we've had an excellent experience with EC2 and S3. Because of our current API interfaces, it made more sense for us to continue with Hadoop rather than explore other options.
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Cloudera
Cloudera is
compatible with Windows operating systems, and Mac allows cloud-based
deployment, it is also very useful to configure data encryption, guarantee
protocols, and security policies. It also provides integrated auditing and
monitoring capabilities, as well as a control comprehensive data repository for
the enterprise, and ensures vendor compatibility through its open-source
architecture.
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Return on Investment
Amazon AWS
  • 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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Cloudera
  • Cloudera products are the most widely. It is more business friendly as data is more secure. The sensitive data that you operate on is local to you and your project rather than processing this data on Cloud.
  • Cloudera is definitely faster as wait time is reduced if on Cloud.
  • A lot range of products are covered. So it is definitely good for businesses and had good returns on investments.
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