Google's Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads with up to 99.999% availability.
$0.03
per month per GB
Azure SQL Database
Score 8.9 out of 10
N/A
Azure SQL Database is Microsoft's relational database as a service (DBaaS).
$0.50
Per Hour
Pricing
Google Cloud BigTable
Azure SQL Database
Editions & Modules
Backup Storage
$0.026
per month per GB
HDD storage
$0.026
per month per GB
SSD storage
$0.17
per month per GB
Nodes
$0.65/hour
per month per node (minimum 1 nodes)
2 vCORE
$0.5044
Per Hour
6 vCORE
$1.5131
Per Hour
10 vCORE
$2.52
Per Hour
Offerings
Pricing Offerings
Cloud BigTable
Azure SQL Database
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Google Cloud BigTable
Azure SQL Database
Features
Google Cloud BigTable
Azure SQL Database
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google Bigtable is ONLY suited for massive data sets which scale PetaBytes and TerraBytes. Anything under this can easily be done via dedicated VMs and open source tools. Google Bigtable is expensive and shall be used wisely. It should be utilised only where it is well suited else you would simply be wasting dollars and not utilizing its full benefits.
Your upcoming app can be built faster on a fully managed SQL database and can be moved into Azure with a few to no application code changes. Flexible and responsive server less computing and Hyperscale storage can cope with your changing requirements and one of the main benefits is the reduction in costs, which is noticeable.
Analytics: is at Google's heart. No on can beat Google in this space and BigTable is one of its implementation of this. The insights you gain from BigTable are simply usable in your day to day activities and can help you make real difference.
Speed: Processing TBs and PBs of data under minutes needs real efficient platform which is capable of doing much more than just processing data. All this data cannot be processed by a single machine, but rather huge pairs of machines working in conjuction with each other. BigTable's implementation is one of the finest and allows you achieve great speeds!
Interface: is great. Google has segregated required task under logically placed buttons which takes no time by users to understand and get habituated.
Scalability is #1: if it used to be an almost no-win endeavour to try to modernize your server or migrate to other hardware, with Azure SQL Database it becomes a press of a button.
All the tools simply work after you are on Azure SQL Database.
The applications do not need changes in order to start using Azure SQL Database.
Hybrid Cloud scenarios will work.
Clustering and failover - already there.
You can start monitoring the use and extract performance insights in a new way in Azure.
User interface's responsiveness: I understand so much is going on under the hood, but laggyness is acceptable if a workload is running or being processed. In case their is not workload being process, GUI should work blazing fast. I have faced this at times, and this becomes frustrating as well.
Nothing other than this - BigTable is quite efficient platform and does exactly what it is built for.
A little slow on processing complex or large Views. We use a lot of Views to feed our BI system, and the processing time could see some improvement, IMHO.
Additional monitoring components would be nice too, automating some built in performance measurement tools would be a nice feature.
Price can always be improved as well. It’s not bad, but room for improvement.
For big IT firms like us, data is very important and it only holds its value if it can make sense to us. Therefore, Bigtable's usability is priceless when it comes to decision making based on data.
We give the support a high rating simply because every time we've had issues or questions, representatives were in contact with us quickly. Without fail, our issues/questions were handled in a timely matter. That kind of response is integral when client data integrity and availability is in question. There is also a wealth of documentation for resolving issues on your own.
Oracle Database is "the" serious database. There really is no competition in that field. SQL Database would be a serious competitor through the ease of implementation and the "no maintenance," but since it's too expensive for "normal" use (medium to small applications), it just priced itself out of the market, so to speak. Nevertheless, we do have 2 or 3 large applications that are highly integrated in azure, and for those it's just too easy to use SQL Database instead of the on premise Oracle Database with VPN gateways etcetera.
We don't need a dedicated SQL dba because so many of the database maintenance operations are managed. A huge positive not only in budget but time constraints.
The ability to scale quickly is the biggest positive as our data needs change constantly.
Easy to migrate from legacy tools and systems, saving us on the need for redevelopment.