MongoDB vs. RabbitMQ

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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It is highly recommended that if you have microservices architecture and if you want to solve 2 phase commit issue, you should use RabbitMQ for communication between microservices. It is a quick and reliable mode of communication between microservices. It is also helpful if you want to implement a job and worker mechanism. You can push the jobs into RabbitMQ and that will be sent to the consumer. It is highly reliable so you won't miss any jobs and you can also implement a retry of jobs with the dead letter queue feature. It will be also helpful in time-consuming API. You can put time-consuming items into a queue so they will be processed later and your API will be quick.

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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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• What RabbitMQ does well is what it's advertised to do. It is good at providing lots of high volume, high availability queue. We've seen it handle upwards of 10 million messages in its queues, spread out over 200 queues before its publish/consume rates dipped. So yeah, it can definitely handle a lot of messages and a lot of queues. Depending on the size of the machine RabbitMQ is running on, I'm sure it can handle more.
• Decent number of plugins! Want a plugin that gives you an interface to view all the queues and see their publish/consume rates? Yes, there's one for that. Want a plugin to "shovel" messages from one queue to another in an emergency? Check. Want a plugin that does extra logging for all the messages received? Got you covered!
• Lots of configuration possibilities. We've tuned over 100 settings over the past year to get the performance and reliability just right. This could be a downside though--it's pretty confusing and some settings were hard to understand.

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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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• It breaks communication if we don't acknowledge early. In some cases our work items are time consuming that will take a time and in that scenario we are getting errors that RabbitMQ broke the channel. It will be good if RabbitMQ provides two acknowledgements, one is for that it has been received at client side and second ack is client is completed the processing part.

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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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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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RabbitMQ is very easy to configure for all supported languages (Python, Java, etc.). I have personally used it on Raspberry Pi devices via a Flask Python API as well as in Java applications. I was able to learn it quickly and now have full mastery of it. I highly recommend it for any IoT project.

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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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I gave it a 10 but we do not have a support contract with any company for RabbitMQ so there is no official support in that regard. However, there is a community and questions asked on StackOverflow or any other major question and answer site will usually get a response.

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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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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.

RabbitMQ has a few advantages over Azure Service Bus 1) RMQ handles substantially larger files - ASB tops out at 100MB, we use RabbitMQfor files over 200MB 2) RabbitMQ can be easily setup on prem - Azure Service Bus is cloud only 3) RabbitMQ exchanges are easier to configure over ASB subscriptions ASB has a few advantages too 1) Cloud based - just a few mouse clicks and you're up and running

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• 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

• Positive: we don't need to keep way too many backend machines around to deal with bursts because RabbitMQ can absorb and buffer bursts long enough to let an understaffed set of backend services to catch up on processing. Hard to put a number to it but we probably save $5k a month having fewer machines around.
• Negative: we've got many angry customers due to queues suddenly disappearing and dropping our messages when we try to publish to them afterward. Ideally, RabbitMQ should warn the user when queues expire due to inactivity but it doesn't, and due to our own bugs we've lost a lot of customer data as a result.
• Positive: makes decoupling the web and API services from the deeper backend services easier by providing queues as an interface. This allowed us to split up our teams and have them develop independently of each other, speeding up software development.

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