Amazon EMR (Elastic MapReduce) vs. Oracle Big Data Cloud Service

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon EMR
Score 8.8 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
Oracle Big Data Cloud Service
Score 6.0 out of 10
N/A
The Oracle Big Data Cloud Services features managed and secure platform cloud service for Apache Hadoop and Apache Spark delivered as an elastic, integrated platform. It provides support for streaming, batch, and interactive analysis.N/A
Pricing
Amazon EMR (Elastic MapReduce)Oracle Big Data Cloud Service
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Amazon EMROracle Big Data Cloud Service
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon EMR (Elastic MapReduce)Oracle Big Data Cloud Service
Features
Amazon EMR (Elastic MapReduce)Oracle Big Data Cloud Service
Platform-as-a-Service
Comparison of Platform-as-a-Service features of Product A and Product B
Amazon EMR (Elastic MapReduce)
-
Ratings
Oracle Big Data Cloud Service
8.1
1 Ratings
3% above category average
Ease of building user interfaces00 Ratings9.01 Ratings
Scalability00 Ratings7.01 Ratings
Platform management overhead00 Ratings9.01 Ratings
Workflow engine capability00 Ratings8.01 Ratings
Platform access control00 Ratings8.01 Ratings
Services-enabled integration00 Ratings8.01 Ratings
Development environment creation00 Ratings9.01 Ratings
Issue recovery00 Ratings7.01 Ratings
Best Alternatives
Amazon EMR (Elastic MapReduce)Oracle Big Data Cloud Service
Small Businesses

No answers on this topic

AWS Lambda
AWS Lambda
Score 8.5 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Red Hat OpenShift
Red Hat OpenShift
Score 9.2 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 8.5 out of 10
Red Hat OpenShift
Red Hat OpenShift
Score 9.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon EMR (Elastic MapReduce)Oracle Big Data Cloud Service
Likelihood to Recommend
8.0
(19 ratings)
10.0
(1 ratings)
Usability
7.0
(4 ratings)
-
(0 ratings)
Support Rating
9.0
(3 ratings)
-
(0 ratings)
User Testimonials
Amazon EMR (Elastic MapReduce)Oracle Big Data Cloud Service
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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Oracle
We use it only when we need to and we have found that the software does what it needs to, it's user friendly and us also really helpful in many other ways as well. Like I mentioned before, we love the security and the speed we receive.
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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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Oracle
  • User friendly
  • Offers support and assistance
  • Worth the cost
  • Time efficient
  • Good reliability
  • Reliable support
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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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Oracle
  • Less pricey
  • Customizable
  • A little more help in setting up/using the systems
  • Constant upgrades are always pricey
  • Some bugs noticable
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Usability
Amazon AWS
Documentation is quite good and the product is regularly updated, so new features regularly come out. The setup is straightforward enough, especially once you have already established the overall platform infrastructure and the aws-cli APIs are easy enough to use. It would be nice to have some out-of-the-box integrations for checking logs and the Spark UI, rather than relying on know-how and digging through multiple levels to find the informations
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Oracle
No answers on this topic
Support Rating
Amazon AWS
I give the overall support for Amazon EMR this rating because while the support technicians are very knowledgeable and always able to help, it sometimes takes a very long time to get in contact with one of the support technicians. So overall the support is pretty good for Amazon EMR.
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Oracle
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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Oracle
Although new, Oracle has been exceptionally good speed wise and the customer service is top notch
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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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Oracle
  • It has had a good impact we are able to complete our projects in time
  • We can save all our data in a safe and secure location
  • Our data analysis is now faster than ever
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ScreenShots