Pub/Sub, simple + reliable + scalable = a great product
Eric Mason | TrustRadius Reviewer
December 14, 2019

Pub/Sub, simple + reliable + scalable = a great product

Score 9 out of 10
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Verified User
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Overall Satisfaction with Google Cloud Pub/Sub

Our company currently uses Pub/Sub to reliably queue up messages that arrive rapidly from multiple instances. It's a very technical product and really only used by the development team rather than company-wide. The primary problem it addresses for us is its ability to handle scale and resilience in the case of errors.
  • Highly scalable.
  • Queues messages for up to 7 days if not acknowledged.
  • Would be nice if the queue could be extended beyond 7 days.
  • We found it a bit tricky replay unacknowledged messages when needed.
  • Pub/Sub has helped avoid data loss improving our customer value prop.
  • Pub/Sub has reduced development time that would otherwise be needed to build a highly scalable queue.
We considered several messaging platforms including Kafka and Kinesis but both would have required more developer work and didn't integrate as nicely with our ecosystem. RabbitMQ is another messaging platform I've researched and prototyped on; it also would have required more developer time to implement as well but might be a good alternative for a hobbyist or a team looking for more customization.
They have decent documentation, but you need to pay for support. We weren't able to answer all our questions with the documentation and didn't have time to setup support before we needed it so I can't give it a higher rating but I think it tends to be a bit slow unless you're a GCP enterprise support customer.

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Scenarios where GCP Pub/Sub is well suited:
- Companies processing large amounts of data where eventual consistency is acceptable and the ability to recover from loss desirable.
- Companies already working with other GCP products (it integrates well with other products in the ecosystem).

Scenarios where GCP Pub/Sub is less well suited:
- If you're not queuing a huge amount of data it's probably overkill.