Google Cloud SQL vs. MongoDB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google Cloud SQL
Score 8.7 out of 10
N/A
Google Cloud SQL is a database-as-a-service (DBaaS) with the capability and functionality of MySQL.
$0
per core hour
MongoDB
Score 8.8 out of 10
N/A
MongoDB is an open source document-oriented database system. 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.
$0
per month
Pricing
Google Cloud SQLMongoDB
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
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Google Cloud SQLMongoDB
Free Trial
YesYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsPricing varies with editions, engine, and settings, including how much storage, memory, and CPU you provision. Cloud SQL offers per-second billing.Fully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
Google Cloud SQLMongoDB
Considered Both Products
Google Cloud SQL
Chose Google Cloud SQL
Our use case was mainly within the Google Cloud ecosystem, so this service was of high value where all of our sub-infra for a project was right there in one place. We no longer had to maintain separate dashboard for monitoring just because our compute and database were on …
Chose Google Cloud SQL
It is easy to connect Google Cloud SQL with the Compute Engine, Cloud Run, BigQuery, or PubSub. The connection inside the Google infrastructure is much more secured and fast when they are in same zone/region, so never faced any issues. The documentation is excellent to connect …
Chose Google Cloud SQL
DigitalOcean managed database is relatively less costly compared to Google Cloud SQL database.

Google Cloud SQL service is well integrated with other Google Cloud Platform services such as IAM which enables fine grain access to team members.
Chose Google Cloud SQL
Simple to implement as SaaS.
Chose Google Cloud SQL
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 …
Chose Google Cloud SQL
Kind of similar features provided against RDS. Used this because of transactional db
Chose Google Cloud SQL
Google's solution for database is, at least for our team, easier to implement and maintain than Amazon's offer.
Chose Google Cloud SQL
Given this is a hosted solution, database a service it helps in removing the effort of maintaining these databases manually. Eases out the pain of upgrading, applying security patches and keeping things running without having to worry about missed changes. The database can be …
Chose Google Cloud SQL
As I used Google Cloud SQL it's performance is very good and it's ui ux is as per the user demand. Apart from it the backend is very strong which makes it more usable tools as it gives or run the query in very minimal time. Yes there has to be some work on security and …
Chose Google Cloud SQL
Google Cloud SQL ended up being less expensive, have a greater support team and offer a much better interface
Chose Google Cloud SQL
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.
Chose Google Cloud SQL
In our experience, we were down for almost a day, because Database Engineers at Rackspace weren't able to understand or provide a solution, and when they did, they had to recreate the database from the scratch. On a server, this is time consuming. When we faced a similar …
Chose Google Cloud SQL
BigQuery is a great analytical database and is generally our first choice for large analytical workloads. While its performance and throughput far outperforms Google Cloud SQL but it supports a far limited dialets of SQL. Generally a significant rewrite will be needed for …
Chose Google Cloud SQL
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 …
Chose Google Cloud SQL
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 …
Chose Google Cloud SQL
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 …
Chose Google Cloud SQL
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 …
Chose Google Cloud SQL
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 …
Chose Google Cloud SQL
- 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 …
Chose Google Cloud SQL
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.
Chose Google Cloud SQL
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
MongoDB
Chose MongoDB
The environment I work in is somewhat unique in that we use both MySQL and MongoDB. However, each is used for specific purposes that the other is not well suited for. MongoDB is not a relational database like MySQL, so it serves as the perfect place to dump key bits of data for …
Chose 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 …
Chose MongoDB
Both Couchbase and MongoDB are document-oriented NoSQL databases, so they have very similar features. While they do have some fundamental differences in terms of how they scale, shard, etc. the one key reason why we went with MongoDB is its availability and support from the …
Chose MongoDB
The flexible structure underlying MongoDB's construction is not found in other competitors; the ability to easily change the structure without affecting other stored documents. It is very ideal for projects that you cannot predict that the structure will change this way. Of …
Chose MongoDB
Implementing new features for application becomes simpler with MongoDB since you don't need to run database migration scripts just to for example add new fields to database only to store some extra data. This is especially good for the deployment phase. Only new version of …
Chose MongoDB
MongoDB is a robust and scalable db which offers a lot of cool features out of the box. Being open sourced and backed by a great community with developer tools like mongo compass , it was a no-brainer to go for it. It has connectors in almost all programming languages and is a …
Chose MongoDB
MongoDB is more of a general purpose nosql database, while elasticSearch is a search engine oriented nosql solution.
Percona Server for MongoDB is a more suitable solution for the enterprise field.
Chose MongoDB
I would say Cassandra is better than MongoDB since it has the backing of Facebook to it. Its inherent properties like versioning put it into the other category of columnar databases, but it's one of the NoSQL databases which you should definitely consider for your organization …
Chose MongoDB
MongoDB is the most reliable and fastest for storing document-based data. It has a place among the most popular DB's these days.
Chose MongoDB
This tool is only capable of reading real-time data very smoothly. The transition was also pretty easy and quick. Syntax is also very easy and comfortable to learn and use.

The main reason for selecting is that it works very fast under the Intellijet module environment and we …
Chose MongoDB
In our early development days we weighed NoSQL databases like MongoDB with RDBMS solutions like MySQL. We were more familiar with MySQL from past experience but also were wary of painful data migrations that slowed down development iterations and increased the risk of outages …
Chose MongoDB
Also, using DocumentDB, and both are good, each was chosen based on the developer's expertise. So take advantage of in-house skills.
Chose MongoDB
Snowflake and Redshift are much more mature and have been around longer. MongoDB is definitely much less expensive and if you are in a startup, this is an almost for-sure option. Redshift can be slow and Mongo is much faster. However, losing the relational database aspect could …
Chose MongoDB
I just felt MongoDB was easier to use and more cost-effective. Aggregation pipelines are great.
Chose MongoDB
It's very fast and easiest to use. Many companies are using this nowadays. It's helped to complete many software products very quickly so the year income has increased compared with last years. Many programmers are now leaning this tool as back end developers so that we changed …
Chose MongoDB
We selected MongoDB because of the following
  • Ease of deployment
  • Use and provisioning on their cloud
Chose MongoDB
MongoDB is our go-to database solution for any project, and the more we work with it the more we love it. Some say that NoSQL is pointless... Our developers wholeheartedly disagree, because they love working with it. Though both NoSQL and SQL have their purposes, in most …
Chose MongoDB
Your default choice should not be MongoDB in my opinion. Most user-facing systems are relational by nature so a well known and reliable SQL database would be easier to maintain and simpler to develop long term. If you highly value speed of development go with firebase. If you …
Chose MongoDB
It does not belong to certain cloud platforms. MongoDB is an independent program that works with any cloud platform including Amazon Web Services and the Google Cloud Platform. For companies who want to maintain a cloud agnostic structure, MongoDB is a great choice for NoSQL …
Chose MongoDB
We wanted to use free ware relational database for our need. MongoDB was perfect fit.
Chose MongoDB
MongoDB and Cassandra are both database system from the NoSQL family. MongoDB can be used in lots of use cases while Cassandra has a specific usage. There are some features that MongoDB provides efficiently while Cassandra doesn't and vice-versa. Like, you can update the data …
Chose MongoDB
We tend to choose MongoDB when we're faced with a particular situation: we know that we need a NoSQL database in general, and want an open-source implementation that allows us to prevent against platform lock-in. Amazon's new DocumentDB product even allows us to choose to use …
Features
Google Cloud SQLMongoDB
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google Cloud SQL
8.9
Ratings
5% above category average
MongoDB
-
Ratings
Automatic software patching9.60 Ratings00 Ratings
Database scalability8.60 Ratings00 Ratings
Automated backups8.70 Ratings00 Ratings
Database security provisions8.50 Ratings00 Ratings
Monitoring and metrics9.00 Ratings00 Ratings
Automatic host deployment9.00 Ratings00 Ratings
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Google Cloud SQL
-
Ratings
MongoDB
10.0
Ratings
13% above category average
Performance00 Ratings10.00 Ratings
Availability00 Ratings10.00 Ratings
Concurrency00 Ratings10.00 Ratings
Security00 Ratings10.00 Ratings
Scalability00 Ratings10.00 Ratings
Data model flexibility00 Ratings10.00 Ratings
Deployment model flexibility00 Ratings10.00 Ratings
Best Alternatives
Google Cloud SQLMongoDB
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google Cloud SQLMongoDB
Likelihood to Recommend
8.4
(0 ratings)
10.0
(0 ratings)
Likelihood to Renew
9.1
(0 ratings)
10.0
(0 ratings)
Usability
8.5
(0 ratings)
10.0
(0 ratings)
Availability
-
(0 ratings)
9.0
(0 ratings)
Support Rating
9.1
(0 ratings)
9.6
(0 ratings)
Implementation Rating
9.1
(0 ratings)
8.4
(0 ratings)
Ease of integration
9.3
(0 ratings)
-
(0 ratings)
User Testimonials
Google Cloud SQLMongoDB
Likelihood to Recommend
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.
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MongoDB [is] great at storing JSON data grouped into "collections". In this format, you can store any JSON documents and conveniently categorize them by collections. The JSON document contained in MongoDB is called binary JSON or BSON and, like any other document in this format, is unstructured. Therefore, unlike traditional DBMS, any kind of data can be stored in collections, and this flexibility is combined with the horizontal scalability of the database. It should be noted that MongoDB does not have links between documents and “collections” (this is partially compensated by the Database Reference - links in the DBMS, but this does not completely solve the problem). As a result, a situation arises in which there is a certain set of data that is not related to other information in the database, and there is no way to combine data from different documents. In SQL systems, this would be an elementary task.
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Pros
  • It has a easily and user understandable interface which provides it every necessary feature to come up with.
  • It's backend is very strong that can help us to run big quieres without any hesitation.
  • It's integration with other tools are one of the powerful feature which makes it more suitable to use.
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  • Easy to learn. When I picked up MongoDB for the first time, I had little background in database management or modeling. If you have a background in javascript (and JSON)... then you can figure out how to use MongoDB pretty fast.
  • Fast performance.
  • It's relatively easy to set up in certain environments because there are lots of ready-made solutions out there.
  • There's a lot of support in the existing ecosystem for it —, especially in the node.js realm.
  • Query syntax is pretty simple to grasp and utilize.
  • Aggregate functions are powerful.
  • Scaling options.
  • Documentation is quite good and versioned for each release.
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Cons
  • Increasing support for more database engines may enable a wider range of application needs to be met.
  • Implementing and updating cutting-edge security features on a constant basis.
  • Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers.
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  • I love the idea of Map-Reduce native support in MongoDB. Admittedly I have not used it as much as I would like -- it always seems to trip me up.
  • Recent additions to the aggregation queries have helped reduce (no pun intended) my need to better wield the weapon that is Map-Reduce.
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Likelihood to Renew
It fits the current needs and bandwith of out lean organization.
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MongoDB is one of the most famous non-relational databases in the world, there are famous active projects that use this database. I think that the same company that develops the database gives you the online induction totally free is something that really is very positive. Accounts with a first-class support to be able to relate the correct implementation of the database, in addition to teaching you the best practices to optimize your projects, I believe that with this decision it is more than obvious which is the best decision at the time of seeing with which database to work.
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Usability
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.
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It is one of the reasons why we prefer it to store documents in a JSON-style format, to access the desired document very quickly regardless of its size, to be readable by human eyes, and to be easily scalable and manageable.
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Support Rating
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.
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I have reached multiple times to the MongoDB community for the help and they have provided each and easy solution for every problem. Over the internet and on stack overflow many people responds over the challenges. Now this tool is very much used in every company and projects so internally many people are there to give a support.
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Implementation Rating
No answers on this topic
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
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.
Read full review
The environment I work in is somewhat unique in that we use both MySQL and MongoDB. However, each is used for specific purposes that the other is not well suited for. MongoDB is not a relational database like MySQL, so it serves as the perfect place to dump key bits of data for quick retrieval later. This is something we can't easily do with MySQL. On this smaller database, MongoDB also lets us retrieve data more quickly with its fast and efficient querying.
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Return on Investment
  • Improved integration with Google Cloud, we have set up some automations with Google Workspace, and we have noticed that the raw data sharing between them is very fast as compared to using some other managed database, not sure why.
  • Due to some downtime during maintenance, we had to set up a relatively small service which ingested the data while this went down and dumped it when it came back up. So this was a negative impact on our ROI, since now we had to remedy this downtime against the same profit margins
  • It was cheaper than the legacy aws service since we needed large database instances
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  • We can make more open and flexible systems due to its easy adaptation to new evolutions in web applications.
  • In the latest versions it offers support for different transactions and we could carry out real tests related to the concurrency of the application.
  • MongoDB allows you to have distributed clusters, which improves the speed of the queries by reducing the latency that exists between the database cluster and the service that executes the query.
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ScreenShots

Google Cloud SQL Screenshots

Screenshot of migrating to a fully managed database solution - Self-managing a database, such as MySQL, PostgreSQL, or SQL Server, can be inefficient and expensive, with significant effort around patching, hardware maintenance, backups, and tuning. Migrating to a fully managed solution can be done using a Database Migration Service with minimal downtime.Screenshot of data-driven application development - Cloud SQL accelerates application development via integration with the larger ecosystem of Google Cloud services, Google partners, and the open source community.

MongoDB Screenshots

Screenshot of Screenshot of Screenshot of Screenshot of Screenshot of Screenshot of