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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Tableau Public
Score 9.8 out of 10
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Tableau Public is a free edition of the Desktop product. With this edition, data can only be published to the Tableau public website and does not allow work to be saved or exported locally.
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Amazon EMR (Elastic MapReduce)
Tableau Public
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Amazon EMR
Tableau Public
Free Trial
No
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
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Community Pulse
Amazon EMR (Elastic MapReduce)
Tableau Public
Features
Amazon EMR (Elastic MapReduce)
Tableau Public
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Amazon EMR (Elastic MapReduce)
-
Ratings
Tableau Public
9.8
12 Ratings
19% above category average
Pixel Perfect reports
00 Ratings
9.710 Ratings
Customizable dashboards
00 Ratings
10.012 Ratings
Report Formatting Templates
00 Ratings
9.712 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Amazon EMR (Elastic MapReduce)
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Ratings
Tableau Public
9.7
12 Ratings
22% above category average
Drill-down analysis
00 Ratings
9.812 Ratings
Formatting capabilities
00 Ratings
9.712 Ratings
Integration with R or other statistical packages
00 Ratings
9.59 Ratings
Report sharing and collaboration
00 Ratings
9.811 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Amazon EMR (Elastic MapReduce)
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Ratings
Tableau Public
9.5
11 Ratings
15% above category average
Publish to Web
00 Ratings
10.011 Ratings
Publish to PDF
00 Ratings
10.09 Ratings
Report Versioning
00 Ratings
9.89 Ratings
Report Delivery Scheduling
00 Ratings
9.69 Ratings
Delivery to Remote Servers
00 Ratings
8.17 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
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.
Tableau public is the best platform to build dashboards for your personal profile and share with recruiters. It's always good to keep ourselves updated on the latest features, create sample dashboards and save them to a personal profile. Tableau public is free and doesn't need any subscription. anyone can create an account and start building reports.
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.
Data visualization: lots of different options, including bar, scatter, pie, waterfall charts to explore relationships between variables, and to present findings/trends to different teams
Integrates readily with limited, though different data sources: TXT, CSV, TDE, Access
Exports reports for review of different dashboards: client-ready/team-ready, with a clean and tidy presentation in PDF format (or hardcopy)
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.
Tableau Public (both Desktop and Server) like their "for a fee" counterparts offer very easy to learn and use tools to transform data into pictures and gain insights into your data. Most organizations report a reduction in development time of 10x vs. other similar tools, due to the intuitive user interface. That said, with Tableau Public, published workbooks are "disconnected" from the underlying data sources and require periodic updates when the data changes. Users are limited to 1 Gb of storage space per user ID and password as well.
I would like to see better options for public sharing of visualizations and data from within the "for a fee" products as more and more organizations are moving in the direction of data sharing with partners and their communities.
It's free, right? I'll keep using the free version. So the real question to ask is this? Will I pay $999 for the Personal version or $1,999 for the Professional? Yikes! That is a big stretch. I'm not sure about that. The product comparison chart is at: http://www.tableausoftware.com/public/comparison
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
Tableau public is a great training tool to understand the basics of Tableau before buying it. A great tool to extend Excel's visualization and to publish data for others. Not useful for anything you need secure. No ability to access databases. Static information only.
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.
Start at the end and work backward. Identify the business case / issue and questions the end users have, then identify the data needed, and where to get it.
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.
Google Charts/Drive is sufficient for simpler data sets, but it does not integrate with other web platforms and the visualization does not look as professional. I'm not aware of any other competitors that offer the same package as Microsoft.
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.