What users are saying about

Amazon EMR

24 Ratings

Google BigQuery

64 Ratings

Amazon EMR

24 Ratings
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Score 8.3 out of 101

Google BigQuery

64 Ratings
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Score 8.8 out of 101

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Likelihood to Recommend

Amazon EMR

Well suited if you quickly want to setup a distributed compute platform, such as Spark. But you have to be advanced enough that you really want to separate compute from data storage. For example, for certain applications packaged solution such as MPP databases (e.g. Redshift) is much easier to set up that Spark on EMR and S3 with the appropriate file formats.
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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
7.6
Automatic software patching
Amazon EMR
Google BigQuery
10.0
Database scalability
Amazon EMR
Google BigQuery
7.4
Automated backups
Amazon EMR
Google BigQuery
7.7
Database security provisions
Amazon EMR
Google BigQuery
8.2
Monitoring and metrics
Amazon EMR
Google BigQuery
5.5
Automatic host deployment
Amazon EMR
Google BigQuery
6.9

Pros

  • Ease of use and ease to setup
  • Autoscaling functionality
  • Integrated into the AWS environment
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  • The web console provides extremely simple interface for test and try.
  • REST API provides capability for integrating with software solutions.
  • The web interface provides useful features like query history, named/saved queries, export results.
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Cons

  • 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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  • If accidentally the return dataset would be humongous (you forget to LIMIT), you cannot really stop a running query, and it'll probably be billed
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Alternatives Considered

Having one of these enterprise edition license comes at its own costs. But, the flexibility to have the cluster spin up with the workbenches and code snippets on the same is really beneficial. Especially, if one had to move out of EMR and consider an option which reduces the debugging time in establishing connections to AWS resources, I would love to used the mentioned three resources on EC2. This would definitely make the processing time to reduce as there is a flexibility to test real time and execute the code snippet and look at the performance and monitor the snippet in real time.
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Comparing to competitors, Google BigQuery has the lowest cost and most flexible pricing model. Definitely higher ROI.
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Return on Investment

  • Better accesss to business data
  • Faster business decisions
  • Better storage and processing
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  • 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.
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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