MongoDB vs. ReadyAPI

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.

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As stated, we do a LOT of API testing, the swaggerhub import makes it easy to add APIs. This is very well-suited, as well as easy management of the steps/cases/suites inside of ReadyAPI. The one thing I do wish ReadyAPI was better suited for is changes to data, we have a lot of test cases in ReadyAPI and if we make a change to how the backend data is structured, one-by-one adjustments need to be made to the steps. Less appropriate, UI testing.

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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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• Ease of use (ability to automatically import API definitions, Jenkins integration for running in the pipeline).
• Detailed test reports (allow to easily identify weak spots during both functional and performance testing).
• One platform for all tests (allows to closely couple and reuse existent tests).

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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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• Needs good documentation
• Need to improve the performance of the tool
• Setup is very complex and for such [a] commercial tool, it should easy and straightforward
• Tool says it supports security testing but in reality, it is not at an extensive level.

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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.

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The only reason this isn't a '10' is because of the cost. This product is definitely meant for organizations who are serious about making sure they invest in the full ecosystem of API design, development, maintenance. But there is a significant cost associated with this investment. and because of this cost (and the non-tangible output for executives), it is a difficult line-item to justify in this post-pandemic environment.

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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.

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SoapUI allows us to combine multiple tests and adhere
to the sequence that they need to run in order to complete successfully.
It has an excellent GUI design and the reporting mechanism is also very
good. It does consume a lot of memory though during concurrent testing

Soap UI has managed to continuously build on it's solid foundation and keep improving by each release. It is by far the most dependable and accurate testing tool out there of its kind. Available via connecting to VM's created as SoapUI test machines give access to it anytime, anywhere practically.

It has an excellent GUI design and the reporting mechanism is also very
good. It does consume a lot of memory though during concurrent testing.

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.

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To be honest, we didnt had much issues with the support, as there is already plenty of online communities available for help. But if ever there were some minor issues with the membership or the certificates, the tech support was always quick and efficient enough to resolve the issue ASAP

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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.

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no very easy but lacks documentation

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.

ReadyAPI provides intuitive GUI capabilities compared to their own open source product. When compared to Postman, ReadyAPI also supports SOAP based services, which is a saver especially when integrating with legacy or other third party systems.

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It has an excellent GUI design and the reporting mechanism is also very
good. It does consume a lot of memory though during concurrent testing. However, I have read that added monitoring tools have been added, which if so the 7 could possibly go to a 8 or 9.

• 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

• Very quick regression testing, hence having the testing results very soon, even the same day of deployment
• for same above reason, it can save money for corporation (so no tedious, costly and erroneous manual testings)
• The test reports are compatible with TestNG, so the corporation can integrate the reports in our Autamation frameworks such as Allure or Jira Zephyr

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