Google offers the Firebase suite of application development tools, available free or at cost for higher degree of usages, priced flexibly accorded to features needed. The suite includes A/B testing and Crashlytics, Cloud Messaging (FCM) and in-app messaging, cloud storage and NoSQL storage (Cloud Firestore and Firestore Realtime Database), and other features supporting developers with flexible mobile application development.
$0.01
Per Verification
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
Firebase
MongoDB Atlas
Editions & Modules
Phone Authentication
$0.01
Per Verification
Stored Data
$0.18
Per GiB
Dedicated Clusters
$57
per month
Dedicated Multi-Reigon Clusters
$95
per month
Shared Clusters
Free
Offerings
Pricing Offerings
Firebase
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
—
—
More Pricing Information
Community Pulse
Firebase
MongoDB Atlas
Considered Both Products
Firebase
Verified User
Consultant
Chose Firebase
Supabase seems to have the best of all worlds right now. Followed by MongoDB/Firebase for smaller projects requiring less manpower and resources. Azure and Microsoft are reserved for existing projects and larger corporate clients.
Firebase is easy to manage and scale really well for web application services. It offers better authentication and is easy to implement. For real-time analytics on web applications, it works very well. Firebase offers more features compared to other services especially it can …
Firebase is well suited for projects with simpler database workloads that require its real-time features. For data that is heavily read in real time, it's a great choice and gives developers a lot of features that would have been complicated and time-consuming to build up front …
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 …
Firebase should be your first choice if your platform is mobile first. Firebase's mobile platform support for client-side applications is second to none, and I cannot think of a comparable cross-platform toolkit. Firebase also integrates well with your server-side solution, meaning that you can plug Firebase into your existing app architecture with minimal effort.
Firebase lags behind on the desktop, however. Although macOS support is rapidly catching up, full Windows support is a glaring omission for most Firebase features. This means that if your platform targets Windows, you will need to implement the client functionality manually using Firebase's web APIs and wrappers, or look for another solution.
It is good if you: 1. Have unstructured data that you need to save (since it is NoSQL DB) 2. You don't have time or knowledge to setup the MongoDB Atlas, the managed service is the way to go (Atlas) 3. If you need a multi regional DB across the world
Analytics wise, retention is extremely important to our app, therefore we take advantage of the cohort analysis to see the impact of our middle funnel (retargeting, push, email) efforts affect the percent of users that come back into the app. Firebase allows us to easily segment these this data and look at a running average based on certain dates.
When it comes to any mobile app, a deep linking strategy is essential to any apps success. With Firebase's Dynamic Links, we are able to share dynamic links (recognize user device) that are able to redirect to in-app content. These deep links allow users to share other deep-linked content with friends, that also have link preview assets.
Firebase allows users to effectively track events, funnels, and MAUs. With this simple event tracking feature, users can put organize these events into funnels of their main user flows (e.g., checkout flows, onboarding flows, etc.), and subsequently be able to understand where the drop-off is in the funnel and then prioritize areas of the funnel to fix. Also, MAU is important to be able to tell if you are bringing in new users and what's the active volume for each platform (Android, iOS).
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.
Attribution and specifically multi-touch attribution could be more robust such as Branch or Appsflyer but understand this isn't Firebases bread and butter.
More parameters. Firebase allows you to track tons of events (believe it's up to 50 or so) but the parameters of the events it only allows you to track 5 which is so messily and unbelievable. So you're able to get good high-level data but if you want to get granular with the events and actions are taken on your app to get real data insight you either have to go with a paid data analytics platform or bring on someone that's an expert in SQL to go through Big Query.
City-specific data instead of just country-specific data would have been a huge plus as well.
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
Firebase functions are more difficult to use, there are no concepts of triggers or cascading deletes without the use of Firebase functions. Firebase functions can run forever if not written correctly and cause billing nightmares. While this hasn't happened to us specifically it is a thing that happens more than one realizes.
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
Our analytics folks handled the majority of the communication when it came to customer service, but as far as I was aware, the support we got was pretty good. When we had an issue, we were able to reach out and get support in a timely fashion. Firebase was easy to reach and reasonably available to assist when needed.
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
Before using Firebase, we exclusively used self hosted database services. Using Firebase has allowed us to reduce reliance on single points of failure and systems that are difficult to scale. Additionally, Firebase is much easier to set up and use than any sort of self hosted database. This simplicity has allowed us to try features that we might not have based on the amount of work they required in the past.
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 started immediately. And the cost is low and easy to justify.
Makes building real-time interfaces easy to do at scale with no backend involvement.
Very low pricing for small companies and green-fields projects.
Lack of support for more complicated queries needs to be managed by users and often forces strange architecture choices for data to enable it to be easily accessed.
