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.
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Amazon Web Services
Score 8.5 out of 10
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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
Pricing
Amazon EMR (Elastic MapReduce)
Amazon Web Services
Editions & Modules
No answers on this topic
Free Tier
$0
per month
Basic Environment
$100 - $200
per month
Intermediate Environment
$250 - $600
per month
Advanced Environment
$600-$2500
per month
Offerings
Pricing Offerings
Amazon EMR
Amazon Web Services
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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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.
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Community Pulse
Amazon EMR (Elastic MapReduce)
Amazon Web Services
Considered Both Products
Amazon EMR
Verified User
Analyst
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 …
Using CI/CD and Cloudformation provides a better way to bring up infrastructure. Triggers like S3 file creation to automatically invoke lambda are missing in other cloud vendors. EMR service allows us to use Big data tools seamlessly. Amazon Web Services team support for …
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.