AWS Elastic Beanstalk vs MongoDB

• AWS Elastic Beanstalk was easy to implement, we only had to insert the application code to have it up and running in a few minutes. This helps us to launch company campaigns for different areas such as marketing, commercial and human resources.
• It has a fast learning curve, since the training material of the platform is public on the manufacturer's portal, furthermore it is easy to interact and intuitive for developers.
• The productivity of the equipment is optimized since they are not worrying about preparing the platform or infrastructure, they only have to attend to what is required by the application and its operation and this maintenance.
• The indicators and metrics that it has, ensure that the application cannot be saturated and have a performance problem, with AWS Elastic Beanstalk the application can scale resources when needed automatically.

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• Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
• You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
• Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.

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• Limited to the frameworks and configurations that AWS supports. There is no native way to use Elastic Beanstalk to deploy a Go application behind Nginx, for example.
• It's not always clear what's changed on an underlying system when AWS updates an EB stack; the new version is announced, but AWS does not say what specifically changed in the underlying configuration. This can have unintended consequences and result in additional work in order to figure out what changes were made.

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• An aggregate pipeline can be a bit overwhelming as a newcomer.
• There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
• Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.

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• Greatly reduced time in setting up and deploying test environments has saved a lot of hours and money.
• Near-zero maintenance means that we don't spend any time tending to servers, the app containers just work.
• The initial learning curve is a little steep to get services hosted in Elastic Beanstalk talking to external services like Redis, MongoDB, etc; but once one understands the pattern, development is a breeze.
• The command line interface has enabled us to build many utility scripts that simplify our development workflow, thereby saving time.

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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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