Amazon API Gateway vs. MongoDB

Experienced a lack of available programming languages while working on a minor project. I had to halt the project and wait for it to be added later. It took ages and had a hit on our productivity. It has a centralized management system which helps and an easy interface which helps to manage multiple tasks in case of large-scale operations and projects.

Incentivized

If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.

Incentivized

• API Gateway integrates well with AWS Lambda. This allows us to build a web server in the language and framework of our choice, deploy it as a Lambda function, and expose it through API Gateway.
• API Gateway manages API keys. Building rate limiting and request quota features are not trivial (or interesting).
• API Gateway's pricing can be very attractive for services that are accessed infrequently.

Incentivized

• 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.

Incentivized

• Client certificates are troublesome when trying to attach them to API GW stages.
• Debugging across several services can be difficult when API GW is integrated with Route 53 and another service like Lambda or EC2/ELB.
• Creating internal/private APIs, particularly with custom domains, can be unintuitive.

Incentivized

• 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.

Incentivized

I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.

Incentivized

NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.

Incentivized

We always had a great experience with the AWS support team. They were always on time and very dependable. It was a good partnership while we worked to resolve our issues.

Incentivized

Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.

Incentivized

While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.

Incentivized

When we tested Azure API Management at the time, it had serious connectivity issues, it was very unstable, and it needed to do a lot using the command line. Comparing with the AWS solution, which was more mature, and the fact that we have services in use on AWS, we ended up choosing to continue using AWS products. This so as not to run the risk of increasing latency in accesses, and of some functionality not working, due to being developed yet.

Incentivized

We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.

• ROI is negative, you need either to hire them to work with you or spend days/weeks to figure out issues.
• For some of the projects in the end it is not worth it, it is just a "buzz" to use serverless but not practical.
• Service is easy to set up authorization and it is easy to manage.

Incentivized

• Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
• You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB