Amazon S3 Glacier vs. MongoDB Atlas

If your organization has a lot of archival data that it needs to be backed up for safekeeping, where it won't be touched except in a dire emergency, Amazon Glacier is perfect. In our case, we had a client that generates many TB of video and photo data at annual events and wanted to retain ALL of it, pre- and post- edit for potential use in a future museum. Using the Snowball device, we were able to move hundreds of TB of existing media data that was previously housed on multiple Thunderbolt drives, external RAIDs, etc, in an organized manner, to Amazon Glacier. Then, we were able to setup CloudBerry Backup on their production computers to continually backup any new media that they generated during their annual events.

Incentivized

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

Incentivized

• Cheap storage of backup data.
• Can be used as a part of the entire suite of tools from Amazon, without requiring you to leave the familiar stack.

Incentivized

• 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.

Incentivized

• Sometime due to slow drives there are operation failure noticed by us in testing
• Cost of restoring data is high and if you have regular restoring them it is not good option and slow as well.
• While we were setting up the system we took some support from AWS and in many cases their answers were not up to the mark.

Incentivized

• 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

Incentivized

It is difficult to delete the data as you have to wait for inventory and then bucket modification has to expire.

Incentivized

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

Incentivized

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

Incentivized

Since the rest of our infrastructure is in Amazon AWS, coding for sending data to Glacier just makes sense. The others are great as well, for their specific needs and uses, but having *another* third-party software to manage, be billed for, and learn/utilize can be costly in money and time.

Incentivized

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.

Incentivized

• We seldom need to access our data in Glacier; this means that it is a fraction of the cost of S3, including the infrequent-access storage class.
• Transitioning data to Glacier is managed by AWS. We don't need our engineers to build or maintain log pipelines.
• Configuring lifecycle policies for S3 and Glacier is simple; it takes our engineers very little time, and there is little risk of errant configuration.

Incentivized

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

Incentivized