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
MongoDB Atlas
Score 8.2 out of 10
N/A
MongoDB Atlas is the company's automated managed cloud service, supplying automated deployment, provisioning and patching, and other features supporting database monitoring and optimization.
$57
per month
Pricing
Google Cloud BigTable
MongoDB Atlas
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)
Dedicated Clusters
$57
per month
Dedicated Multi-Reigon Clusters
$95
per month
Shared Clusters
Free
Offerings
Pricing Offerings
Cloud BigTable
MongoDB Atlas
Free Trial
No
No
Free/Freemium Version
No
Yes
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
MongoDB Atlas
Considered Both Products
Cloud BigTable
No answer on this topic
MongoDB Atlas
Verified User
Anonymous
Chose MongoDB Atlas
In general, they all compete against each other, and each solution has its own advantages and disadvantages. While MongoDB Atlas was the way to go for some cases, however, other databases were more fit for some services that MongoDB Atlas, especially if they were managed by us, …
MongoDB Atlas has been in the market for very long time and there are bunch of documentation, training and support for it. It also is specifically designed for the use case similar to our project and big companies in the market uses them for very high load which made us …
Both AWS RDS and MongoDB Atlas provide a state-of-the-art managed database hosting service, with the difference being the type of databases they support. AWS RDS does not support MongoDB engine and Atlas only supports MongoDB. So I consider them complimentary services and we …
MongoDB Atlas has an excellent rating out there in the market. They have a great supporting team as well. When we have questions about technical stuff, they respond fast. The performance of MongoDB Atlas is the key factor that we choose to use. Because it has such an easy way …
Vice President, Chief Architect, Development Manager and Software Engineer
Chose MongoDB Atlas
MongoDB is a great product but on premise deployments can be slow. So we turned to Atlas. We also looked at Redis Labs and we use Redis as our side cache for app servers. But we love using MongoDB Atlas for cloud deployments, especially for prototyping because we can get …
When choosing a NoSQL, open source database, MongoDB is the clear winner from an implementation standpoint. For databases that are better suited for highly-organized data, a traditional database engine like MySQL, PostgreSQL, or Oracle's RDBMS may be a better choice. When the …
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.
I would recommend MongoDB Atlas to every company who have a significant need in the NoSQL database and do not want to manage their infrastructure. Using MongoDB Atlas can significantly reduce your management time and cost, which saves valuable resources for other tasks. It also suits a smaller company as MongoDB Atlas scales up and down very quickly.
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.
Generous free and trial plan for evaluation or test purposes.
New versions of MongoDB are able to be deployed with Atlas as soon as they're released—deploying recent versions to other services can be difficult or risky.
As the key supporters of the open source MongoDB project, the service runs in a highly optimized and performant manner, making it much easier than having to do the work internally.
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.
For someone new, it could be challenging using MongoDB Atlas. Some official video tutorials could help a lot
Pricing calculation is sometimes misleading and unpredictable, maybe better variables could be used to provide better insights about the cost
Since it is a managed service, we have limited control over the instances and some issues we faced we couldn't;'t know about without reaching out to the support and got fixed from their end. So more control over the instance might help
The way of managing users and access is somehow confusing. Maybe it could be placed somewhere easy to access
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.
I would give it 8. Good stuff: 1. Easy to use in terms of creating cluster, integrating with Databases, setting up backups and high availability instance, using the monitors they provide to check cluster status, managing users at company level, configure multiple replicas and cross region databases. Things hard to use: 1. roles and permissions at DB level. 2. Calculate expected costs
We love MongoDB support and have great relationship with them. When we decided to go with MongoDB Atlas, they sent a team of 5 to our company to discuss the process of setting up a Mongo cluster and walked us through. when we have questions, we create a ticket and they will respond very quickly
In general, they all compete against each other, and each solution has its own advantages and disadvantages. While MongoDB Atlas was the way to go for some cases, however, other databases were more fit for some services that MongoDB Atlas, especially if they were managed by us, which means less cost, like Redis for example
