Google Cloud BigTable vs. MongoDB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Cloud BigTable
Score 8.7 out of 10
N/A
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
MongoDB
Score 8.6 out of 10
N/A
MongoDB (from "humongous") is an open source document-oriented database system developed and supported by 10gen. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster. According to the vendor, organizations from cutting…
$0.10
million reads
Pricing
Google Cloud BigTableMongoDB
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)
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Cloud BigTableMongoDB
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsFully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
Google Cloud BigTableMongoDB
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
Google Cloud BigTableMongoDB
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google Cloud BigTable
8.8
1 Ratings
MongoDB
-
Ratings
Automatic software patching8.01 Ratings00 Ratings
Database scalability10.01 Ratings00 Ratings
Automated backups9.01 Ratings00 Ratings
Database security provisions8.01 Ratings00 Ratings
Monitoring and metrics9.01 Ratings00 Ratings
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Google Cloud BigTable
-
Ratings
MongoDB
9.1
38 Ratings
Performance00 Ratings9.138 Ratings
Availability00 Ratings9.538 Ratings
Concurrency00 Ratings8.438 Ratings
Security00 Ratings8.738 Ratings
Scalability00 Ratings9.638 Ratings
Data model flexibility00 Ratings9.038 Ratings
Deployment model flexibility00 Ratings9.237 Ratings
User Ratings
Google Cloud BigTableMongoDB
Likelihood to Recommend
9.0
(1 ratings)
9.3
(78 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(67 ratings)
Usability
9.0
(1 ratings)
9.0
(14 ratings)
Availability
-
(0 ratings)
9.0
(2 ratings)
Support Rating
9.0
(1 ratings)
9.5
(15 ratings)
Implementation Rating
-
(0 ratings)
8.4
(4 ratings)
User Testimonials
Google Cloud BigTableMongoDB
Likelihood to Recommend
Google
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.
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MongoDB
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
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Pros
Google
  • 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.
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MongoDB
  • Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
  • You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
  • Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
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Cons
Google
  • 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.
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MongoDB
  • An aggregate pipeline can be a bit overwhelming as a newcomer.
  • There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
  • Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
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Likelihood to Renew
Google
No answers on this topic
MongoDB
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
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Usability
Google
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.
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MongoDB
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
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Support Rating
Google
Google provides premium support services for BigTable which is absolutely blazing fast similar to Bigtable's performance.
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MongoDB
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
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Implementation Rating
Google
No answers on this topic
MongoDB
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
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Alternatives Considered
Google
No answers on this topic
MongoDB
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
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Return on Investment
Google
  • Positive return on investment.
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MongoDB
  • Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
  • You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
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