Google Cloud SQL is a database-as-a-service (DBaaS) with the capability and functionality of MySQL.
$0
per core hour
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 SQL
MongoDB Atlas
Editions & Modules
License - Express
$0
per core hour
License - Web
$0.01134
per core hour
Storage - for backups
$.08
per month per GB
HA Storage - for backups
$.08
per month per GB
Storage - HDD storage capacity
$.09
per month per GB
License - Standard
$0.13
per core hour
Storage - SSD storage capacity
$.17
per month per GB
HA Storage - HDD storage capacity
$.18
per month per GB
HA Storage - SSD storage capacity
$.34
per month per GB
License - Enterprise
$0.47
per core hour
Memory
$5.11
per month per GB
HA Memory
$10.22
per month per GB
vCPUs
$30.15
per month per vCPU
HA vCPUs
$60.30
per month per vCPU
Dedicated Clusters
$57
per month
Dedicated Multi-Reigon Clusters
$95
per month
Shared Clusters
Free
Offerings
Pricing Offerings
Google Cloud SQL
MongoDB Atlas
Free Trial
Yes
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Pricing varies with editions, engine, and settings, including how much storage, memory, and CPU you provision. Cloud SQL offers per-second billing.
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More Pricing Information
Community Pulse
Google Cloud SQL
MongoDB Atlas
Considered Both Products
Google Cloud SQL
Verified User
Anonymous
Chose Google Cloud SQL
Google Cloud SQL ended up being less expensive, have a greater support team and offer a much better interface
I 100% prefer Google Cloud SQL over Amazon Aurora in terms of ease of use and clarity in terms of understanding how the autoscaling is going to work. Connecting to the database directly is also much more straightforward.
Setting up or migrating Google Cloud SQL is easy as compared to AWS. It has a good monitoring and logging mechanism and a good user interface which makes it easy to navigate.It also has a pay as you go pricing which makes it easier to reduce cost. Google Cloud SQL offers …
Actually Google Cloud SQL is similar to them, the difference is which engine each supports e.g. there's no managed Oracle DB in Google Cloud SQL but as long as you don't need Oracle, Google Cloud SQL should suffice and give you great user experience and performance. You also …
Google SQL was great as a first SQL provision. It quickly enabled the apps to be built and scaled as needed for a while. It was robust and adaptable as needed and easy to export as needed when ready, depending on growth. Cost-wise, it's a good choice and requires little …
Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google …
When comparing cost, Google Cloud SQL typically offers a more straightforward and versatile plan than Azure SQL Database. Cloud SQL for PostgreSQL is a serverless solution provided by Google Cloud SQL that automatically modifies resources according to workload. For customers …
- AWS RDS and Aurora is a just a notch above Google Cloud SQL as it provide boost in performance when required - Google Cloud SQL Mysql Engine is Cloud based and better than native Mysql as it provides management of the server out of box - Compared to a MongoDB it has a low …
At first, we choose Google Cloud SQL only for demo purposes. It is so easy to set up and It is fully managed. we have worked with Azure SQL as well but Google SQL is more simple to use and It fully secure, reliable, provides high availability, and very Low Latency.
Easier learning, simple features and settings with a very user-friendly application environment and flexible prices make Google Cloud [SQL] a pioneering option over competitors
Google Cloud SQL is just as good as the other guys. We were already invested in GCP, which made the choice very easy. We did not want to start fresh in AWS or Azure. We used our existing GCP setup and just added Cloud SQL. It's unfortunate that companies continue to send people …
There are many options for cloud-hosted dedicated SQL instances. In many ways, simply moving from software and server-based database to a dedicated cloud database is just generally good. All hosts provide some sort of scaling and backup, and all separate the server management …
Google Cloud SQL is very similar to other cloud provider options. AWS and DigitalOcean are direct competitors, While Azure is focusing on their own products. At cloud provider level, it's a matter of choosing the provider, and this product will not play a significant role on …
The Google Cloud SQL offering fits into our development stack and was a clean replacement for our MySQL database. If we had been using SQL Server instead, then the offering from Azure would have made more sense. I have used both in the past and both work well, with GCP being …
It's dramatically faster than running MySQL on a VM, which is what we did before. Whatever Google has done to optimize Google Cloud SQL compared to standalone MySQL installations has worked.
I've used supabase and can say that Google Cloud SQL is a lot more hands off. They just run an instance for you and don't do much more than that. Which is exactly what we wanted. If you want something that is truly fully managed and abstracted then I guess that would be a …
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 …
Does what it promises well, for instance, as a sidecar for the main enterprise data warehouse. However, I would not recommend using it as the main data warehouse, particularly due to the heavy business logic, as other dedicated tools are more suitable for ensuring scalable operations in terms of change management and multi-developer adjustments.
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.
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.
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
As with other cloud tools, users must learn a new terminology to navigate the various tools and configurations, and understand Google Cloud's configuration structure to perform even the most basic operations. So the learning curve is quite steep, but after a few months, it gets easier to maintain.
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
GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.
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
Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google Cloud SQL with its nature and support.
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