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26 Ratings
69 Ratings
26 Ratings
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Score 8.3 out of 101
69 Ratings
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Score 8.6 out of 101

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Likelihood to Recommend

Amazon EMR

Amazon Elastic MapReduce is useful in cases where two conditions are met. First, that you are planning on using multiple big data tools simultaneously to analyze big data sets. And second, that you need a tool that simplifies managing big data tools. If these two conditions are met, MapReduce does a great job. The user interface is simple. The program eliminates some programming requirements. The software also makes setting up big data analyses much easier. With these benefits acknowledged, MapReduce is not a good tool for "small" data analyses, given that there are other tools that do the job quicker and much more professional output. If you're on the fence, try out MapReduce with competing "small" data tools and see if you really need big data software.
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Google BigQuery

- If you are using Google Analytics and there is huge data that is getting streamed every day then you must have Big Query and use it for analysis. It is not only helpful for analysis but also for debugging your Google Analytics implementations.- For analyzing a small dataset you don't need Big Query you can use normal MySQL on your own premises. Analyzing on Un-structured data is not possible with Big Query.
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Feature Rating Comparison

Database-as-a-Service

Amazon EMR
Google BigQuery
7.7
Automatic software patching
Amazon EMR
Google BigQuery
10.0
Database scalability
Amazon EMR
Google BigQuery
7.5
Automated backups
Amazon EMR
Google BigQuery
7.6
Database security provisions
Amazon EMR
Google BigQuery
9.1
Monitoring and metrics
Amazon EMR
Google BigQuery
5.3
Automatic host deployment
Amazon EMR
Google BigQuery
6.5

Pros

  • 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.
Thomas Young profile photo
  • Processing of huge volumes of data enabled us to provide strategic insights by understanding the facts and realities.
  • Detailed Audience analysis enabled us to achieve better targeting for digital media and marketing campaigns
  • Personalization: We are able to achieve personalization by marrying, stitching, and processing huge volume of data.
Gaurav Gautam profile photo

Cons

  • The analytical processes generally run quicker with the standalone tools of Hadoop, Spark, and others. If you only use one big data tool and don't really need things simplified, then Elastic MapReduce is more of an overhead tool that doesn't add much value.
  • The analytical capabilities of Elastic MapReduce are nowhere near as complex or broad as non-big data tools. I would suggest not using the tool unless your data really is big data.
  • The machine learning capabilities of Elastic MapReduce (using the big data tools of Hadoop/Spark) are good but are not as easy to use as other machine learning tools.
Thomas Young profile photo
  • Documentation is not complete, sometimes not clear.
  • Performance is unstable occasionally.
  • Error message not clear.
Charles Chao profile photo

Alternatives Considered

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 has a very nice user interface. Additionally, Elastic MapReduce runs fairly quickly and the results are generally easier to manipulate. With this said, Elastic MapReduce is definitely not the easiest nor quickest tool for big data analytics.
Thomas Young profile photo
We liked BQ because the cost of it is only dependent on the amount of data you store (and there are tiers of data access) and how much you search. For us, it is significantly less expensive to run BQ than an equivalent hosted RDBMS. Because most of our data pipelines are automated, and, we only need to do ad-hoc queries irregularly, BQ fit our criteria very well.
Anatoly Geyfman profile photo

Return on Investment

  • Amazon Elastic MapReduce has had a positive ROI in the sense that it saved time managing big data projects where analysts were using different big data tools. Essentially, an increase in employee productivity.
  • Elastic MapReduce is not worth it in cases where you're just trying things out. You'll likely lose money unless you're sure that using MapReduce is a good idea.
  • Elastic MapReduce takes some time learning, although not too much. If the employee is less well-versed in big data analytics, the software is a high hill to climb that eats up employee time.
Thomas Young profile photo
  • Increased employee efficiency: interactive analytical queries can run much faster on BigQuery, problems are discovered/identified quicker.
  • KPI reports are delivered to management much quicker.
  • Overall reduced cost for BlueCava.
Charles Chao profile photo

Pricing Details

Amazon EMR

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Google BigQuery

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details