Amazon S3 vs MongoDB

• Highly available and redundant; we do not worry about the service having downtime
• Simple usage from multiple different frameworks using Amazon's SDKs, or roll your own
• A large number of bucket policies and security adjustments to tailor usage to customer needs
• Regional support for storing assets in particular locations around the world

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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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• No support for object versions retention: There can be a retention policy(days or number) for object versions that are stored in S3 so that we don't have to worry about paying extra for all the old versions of an object in the bucket.
• No feature for replication within a region: Currently AWS does not support replication within a region. Also, having to enable versioning for buckets in which you need replication makes it even more costly.
• Confusing pricing: The pricing model of S3 can be a little confusing for a new customer with questions regarding data transfer from other AWS services, between buckets or data transfer to the outside world.

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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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• It practically eliminated some real heavy storage servers from our premises and reduced maintenance cost.
• The excellent durability and reliability make sure the return of money you invested in.
• If the objects which are not active or stale, one needs to remove them. Those objects keep adding cost to each billing cycle. If you are handling a really big infrastructure, sometimes this creates quite a huge bill for preserving un-necessary objects/documents.

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• Much faster development time.
• Price is fantastic compared to MSSQL when you consider OS costs and the entire package.
• Only negative to me is the lack of DBA skills for it, due to it being a new player in the field. I feel like that will get better as time moves on however.

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