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
Percona Operator
Score 9.1 out of 10
N/A
The Percona Kubernetes Operator for Percona XtraDB Cluster or Percona Server for MongoDB automates the creation, alteration, or deletion of members in a Percona XtraDB Cluster or Percona Server for MongoDB environment. It can be used to instantiate a new Percona XtraDB Cluster or Percona Server for MongoDB replica set, or to scale an existing environment. The Operator contains all necessary Kubernetes settings to provide a proper and consistent Percona XtraDB Cluster or Percona Server for…
N/A
Pricing
MongoDB Atlas
Percona Operator
Editions & Modules
Dedicated Clusters
$57
per month
Dedicated Multi-Reigon Clusters
$95
per month
Shared Clusters
Free
No answers on this topic
Offerings
Pricing Offerings
MongoDB Atlas
Percona Operator
Free Trial
No
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
—
Free and open-source
More Pricing Information
Community Pulse
MongoDB Atlas
Percona Operator
Considered Both Products
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 …
For a long time we struggled finding a viable solution to migrate our existing db workloads inside Kubernetes. Before "operators era" proper db workloads required manual management, of course that easily raised administrative overhead. Then the future started to be brighter …
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.
Production ready, robust DB solution built for Kubernetes envs, we was able, for the first time, to ship production db workloads inside k8s. Be sure to check differences with "traditional" MySQL and other clustering solutions. Also be sure to match it with proper k8s storage solutions.
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
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
Easy and fast deployment. A reliable, fully automated, high-available db lifecycle management solution. It requires a bit of learning time for people new to operators ecosystem.
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
For a long time we struggled finding a viable solution to migrate our existing db workloads inside Kubernetes. Before "operators era" proper db workloads required manual management, of course that easily raised administrative overhead. Then the future started to be brighter with the introduction of operators and the "official" Oracle's MySQL Operator, then Presslab's one, finally Percona's operator. Compared to other operators, the last one allowed us to ship production db workloads inside k8s.