IBM Cloudant vs Google BigQuery

• For us, performance and scalability is the key, and Cloudant DB backed by CouchDB is scalable and performant.
• IBM Cloudant dB is very easy to provision for sandbox, development, QA as well as production.
• Support for Java for CouchDB app server analytics enables a greater control for over developers.
• Schema free oriented very easy to program and build applications on it.
• We love it!!

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• How many pros can a person type? This storage program gives workers and students the reality of unlimited storage space. I have never came close to overfilling my google cloud storage because it's huge and the best. I can view anything I save on there from any of my internet devices which is very important.
• Depending on how you have the program set up - either online or through an application that lives on your desktop, dragging and dropping files to and from Cloud Storage couldn't be any more uncomplicated. Plus, new users who meet certain criteria - like updating personal security, or share the program receive additional free online storage.
• The array of tools is very impressive, intuitive to use, and well organized in the sense that you don't have to go looking for individual apps. They're all easily accessed via a single dropdown.

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• It was only after we went with the cloud-based solution that IBM rolled out an on-premise version.
• We found that a 3rd-party ODBC driver was required for a few applications that needed to pull data out of Cloudant.
• The sales process was difficult because the salesperson we used was not as versed on Cloudant as I had hoped.

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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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• Saving in-terms of cost of procuring and maintaining hardware, which will be realized over the next 5 years.
• Positive ROI in terms of the number of FTEs involved in maintaining our databases; our DBAs can now focus on other important and business critical applications.
• Best ROI in terms of our organization's vision - they are no longer anxious / nervous to move to the cloud. We are already on the CLOUD.

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• Google BigQuery has had enormous impact in terms of ROI to our business, as it has allowed us to ease our dependence on our physical servers, which we pay for monthly from another hosting service. We have been able to run multiple enterprise scale data processing applications with almost no investment
• Since our business is highly client focused, Google Cloud Platform, and BigQuery specifically, has allowed us to get very granular in how our usage should be attributed to different projects, clients, and teams.
• Plain and simple, I believe the meager investments that we have made in Google BigQuery have paid themselves back hundreds of times over.

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