Over a million developers have joined DZone.

MongoDB as a Message Queue

· Java Zone

Microservices! They are everywhere, or at least, the term is. When should you use a microservice architecture? What factors should be considered when making that decision? Do the benefits outweigh the costs? Why is everyone so excited about them, anyway?  Brought to you in partnership with IBM.

This is a live blog from MongoSV. Here’s a link to the entire series of posts.
About.me uses MongoDB for different pieces of infrastructure, but this talk is just about queuing.

Originally ran a 3-node RabbitMQ cluster, without disk persistence. Were having trouble diagnosing issues at scale. Looked at some other AMQP options, but decided on MongoDB.

Benefits: async ops, per-message (document) atomicity, batch processing, periodic processing, durability, sharding, operational familiarity (n.b. that would be the big one for me!). One drawback: AMQP push model needs to be emulated with MongoDB polling. To model topic matching, they’re using a regex. One thing they don’t (can’t) do with Mongo: fanout.

Use a capped collection? It has better performance but is limited to a single node and FIFO. They use an uncapped collection: can shard. Can get semi-FIFO but not strict.

Implementation:

Each message is a document. To create a message, just insert. The document has a queue field (string id) and a payload (serialized data).

To consume a message they use a findAndModify to grab and remove a document atomically. They index on (queue, _id).

That’s pretty much it! This would be pretty simple to implement in any language (he’s showing an example in the shell + in Python).

Benchmarks they ran showed MongoDB outperforming RabbitMQ for message creation by 19% (this is a single-node benchmark on a laptop, FYI). For consumption MongoDB again does very well (outperforming RabbitMQ for different levels of concurrency).

FindAndModify is blocking, so you will see high lock % w/ lots of concurrent consumers.

Pros and Cons

Pro: familiar, sharding, durability/persistence, low operational overhead, optional use of advanced queries.

Cons: Not AMQP, needs to poll, performance depends on polling frequency + concurrency, fewer libraries available (for Python there’s a library called Kombu), locking for findAndModify.


Source:  http://blog.fiesta.cc/post/13984644719/live-blogging-mongosv-mongodb-as-a-message-queue

Discover how the Watson team is further developing SDKs in Java, Node.js, Python, iOS, and Android to access these services and make programming easy. Brought to you in partnership with IBM.

Topics:

Opinions expressed by DZone contributors are their own.

The best of DZone straight to your inbox.

SEE AN EXAMPLE
Please provide a valid email address.

Thanks for subscribing!

Awesome! Check your inbox to verify your email so you can start receiving the latest in tech news and resources.
Subscribe

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}