Amazon EMR (Elastic MapReduce) vs. Datameer

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
Datameer
Score 8.5 out of 10
N/A
Datameer helps businesses clean up, combine, and organize data to make sense of it and use it for reports and machine learning.N/A
Pricing
Amazon EMR (Elastic MapReduce)Datameer
Editions & Modules
No answers on this topic
Team/Enterprise
Contact for pricing
per month Team
Offerings
Pricing Offerings
Amazon EMRDatameer
Free Trial
NoYes
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)Datameer
Considered Both Products
Amazon EMR
Chose Amazon EMR (Elastic MapReduce)
Perhaps the biggest advantage Amazon Elastic MapReduce has over competing big data management software is the user base. Elastic MapReduce, compliments of its connection with Amazon, has a large user base to whom questions about functionality can be addressed. The software also …
Datameer

No answer on this topic

Top Pros
Top Cons
Best Alternatives
Amazon EMR (Elastic MapReduce)Datameer
Small Businesses

No answers on this topic

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User Ratings
Amazon EMR (Elastic MapReduce)Datameer
Likelihood to Recommend
8.4
(19 ratings)
9.0
(9 ratings)
Likelihood to Renew
-
(0 ratings)
6.4
(7 ratings)
Usability
8.3
(3 ratings)
9.0
(1 ratings)
Support Rating
9.0
(3 ratings)
8.0
(1 ratings)
User Testimonials
Amazon EMR (Elastic MapReduce)Datameer
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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Datameer
Datameer is a great tool if someone is capable of keeping the most recent version of the tool up to date along with the most recent version of the distribution of Hadoop. The tool is easy to support but it must have someone who can run the back end processes
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Pros
Amazon AWS
  • Amazon Elastic MapReduce works well for managing analyses that use multiple tools, such as Hadoop and Spark. If it were not for the fact that we use multiple tools, there would be less need for MapReduce.
  • MapReduce is always on. I've never had a problem getting data analyses to run on the system. It's simple to set up data mining projects.
  • Amazon Elastic MapReduce has no problems dealing with very large data sets. It processes them just fine. With that said, the outputs don't come instantaneously. It takes time.
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Datameer
  • It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT.
  • It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization .
  • Excel feature is awesome for business users which is already provided by Datameer.
  • Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation.
  • Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash.
  • It can be used in premise or in a cloud computing environment.
  • Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem.
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Cons
Amazon AWS
  • Sometimes bootstrapping certain tools comes with debugging costs. The tools provided by some of the enterprise editions are great compared to EMR.
  • Like some of the enterprise editions EMR does not provide on premises options.
  • No UI client for saving the workbooks or code snippets. Everything has to go through submitting process. Not really convenient for tracking the job as well.
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Datameer
  • Concentration issues are possible while using a lot of tabs at once.
  • In most cases, the length of a tutorial video is excessive.
  • A more condensed design is certainly a viable option.
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Likelihood to Renew
Amazon AWS
No answers on this topic
Datameer
Employees with intermediate SQL and Hive knowledge can generate reports faster than using Datameer . It does have visualization tool but I don't think it is anything that cannot be accomplished by importing the data in Excel
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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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Datameer
Easy to use for most things, starts to require some planning as your projects get more complex.
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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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Datameer
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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Datameer
Pricing, support, and ease of use. We plan to scale up our data over the net few years and Datameer gives us all the things we need in one tool. Handles large transformations quickly and works with all the cloud data warehouses.
Datameer's per-user pricing sealed the deal for us as we plan to transfer much more data over the next few years. We looked at Fivetran but the usage pricing discourages growth. We also looked at Informatica but it was too expensive and didn't work as well with other BI tools like Datameer does.
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Return on Investment
Amazon AWS
  • Positive: Helped process the jobs amazingly fast.
  • Positive: Did not have to spend much time to learn the system, therefore, saving valuable research time.
  • Negative: Not flexible for some scenarios, like when some plugins are required, or when the project has to be moved in-house.
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Datameer
  • We have not been able to reach our business objectives just yet.
  • Hadoop its a hard sell in most companies still.
  • Legacy skills are still highly on demand and as long as an easier path leverage SQL for example is available, it would be hard to gain more adoption.
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ScreenShots

Datameer Screenshots

Screenshot of DATA TRANSFORMATION: SQL or No Code

SQL SELECT statements can be used to explore and shape data. Work is represented visually on a canvas like interface, making it easier to design and maintain projects.

Datameer includes library of pre-built drag-and-drop transformations to accelerate SQL development or transform datasets without writing code.Screenshot of DATA CATALOG: Collaboration in Snowflake

Search, Metadata, Data Profiling, and Auto documentationScreenshot of AUTOMATION & INSIGHTS

Insights can be sent to email or Slack, integrated, and deployed to SnowflakeScreenshot of PRODUCTION PIPELINES: From ad-hoc exploration to production pipelines

GIT version control, materialization, dependency management, monitoring