MongoDB Atlas vs. Percona Operator

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

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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.

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• Easy and fast deployment.
• A reliable, fully automated, high-available db lifecycle management solution.
• Exaustive documentation.
• Production ready.

• 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

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• Some differences compared to "traditional" MySQL solution.
• Had some hard times trying to use it combined with pre-existing techs like WordPress, Magento, etc.
• The specific k8s environment features can have an impact on it, like the storage solutions offered by the cloud vendor.

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

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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

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Well documented, there was no need to contact support.

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.

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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.

• Positive - Faster provisioning so we don't have development teams waiting.
• Positive - Automated backups and server management - eliminates need for dedicated DBAs.

Incentivized

Independently Invited by TrustRadius

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• It allowed us to use k8s on our entire infrastructure.
• Decreased administrative overhead around our db services.
• As it is an open source technology, it cut down our db pricings.