What users are saying about

Amazon DynamoDB

Top Rated
52 Ratings

Google BigQuery

64 Ratings

Amazon DynamoDB

Top Rated
52 Ratings
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Score 8.2 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 DynamoDB

It is best for high demand over short periods of time and then being scaled down to save costs. This is kind of a pay for what you need model. This falls short though because while you can scale up unlimited you can only scale down 4 times a day which can be a limitation for some.
Adam Lauer profile photo

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

NoSQL Databases

Amazon DynamoDB
7.9
Google BigQuery
Performance
Amazon DynamoDB
8.0
Google BigQuery
Availability
Amazon DynamoDB
8.4
Google BigQuery
Concurrency
Amazon DynamoDB
9.0
Google BigQuery
Security
Amazon DynamoDB
8.7
Google BigQuery
Scalability
Amazon DynamoDB
9.7
Google BigQuery
Data model flexibility
Amazon DynamoDB
4.0
Google BigQuery
Deployment model flexibility
Amazon DynamoDB
7.3
Google BigQuery

Database-as-a-Service

Amazon DynamoDB
Google BigQuery
7.6
Automatic software patching
Amazon DynamoDB
Google BigQuery
10.0
Database scalability
Amazon DynamoDB
Google BigQuery
7.4
Automated backups
Amazon DynamoDB
Google BigQuery
7.7
Database security provisions
Amazon DynamoDB
Google BigQuery
8.2
Monitoring and metrics
Amazon DynamoDB
Google BigQuery
5.5
Automatic host deployment
Amazon DynamoDB
Google BigQuery
6.9

Pros

  • Fast retrieval
  • Auto scaling to control costs
  • Query and scanning allow for different use cases
Adam Lauer profile photo
  • Big Query is fast and based on the cloud you can run your query on a huge dataset. Huge means data in TB's. This also reduces the company cost to build that kind of infrastructure to store data.
  • Not specific to Google Analytics but you can import data from different sources for analysis purpose and use the power of the cloud to run the query.
  • Not much time to learn - You don't need any special skills, just SQL and you can use Big Query for your use. Learning SQL is not a big task you can learn it in a week.
  • Big Query refrence schema and different sample query are available to practice on queries.
  • Google also provide sample dataset to use then purchase Big Query.
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Cons

  • Ease of use, I had to search several non-Amazon tutorials to figure out setup.
  • Integration into RDBMS would be a great improvement. Currently to move data around you have to export it and reimport into your destination. You could use Amazon Data Migration services - but not very straight forward.
  • You only have once instance. If you want to group tables into a "database", you cannot do that.
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  • Though it is SQL some syntax are different but they are getting used to after you use for some time.
  • The legacy SQL is in beta state but can be used and you can run the query with simple SQL.
  • More documentation is needed for using User-defined functions in Big Query.
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Likelihood to Renew

Amazon DynamoDB6.9
Based on 13 answers
I wouldn't stay with the product, but may simply because I have no other choice. The reason for keeping it will depend on if we are given time by management to go to another solution (back to an SQL database) or the purchase of an ETL tool.
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No score
No answers yet
No answers on this topic

Alternatives Considered

We ended up selecting DynamoDB compared to similar products simply because we host on AWS. To use any other NoSQL solution would require more work in the long run due to having to maintain the EC2 instance, manage updates to the operating system and whatever NoSQL system that was chosen.
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Comparing to competitors, Google BigQuery has the lowest cost and most flexible pricing model. Definitely higher ROI.
Charles Chao profile photo

Return on Investment

  • The system is free to use (to a point).
  • The system was relatively easy to get setup to add data.
  • The system is difficult to access data without the use of scripts to handle return of data (unless you utilize an ETL tool).
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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.
Charles Chao profile photo

Pricing Details

Amazon DynamoDB

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