Google Cloud Pub/Sub Reviews & Insights

Score8.8 out of 10

28 Reviews and Ratings

Community insights

TrustRadius Insights for Google Cloud Pub/Sub are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.

Pros

Ease of Use and Scalability: Users have appreciated the ease of use and scalability offered by the data streaming service. They found it intuitive to navigate and were able to easily scale their operations as needed.

Valuable Dead Letter Queue Functionality: Some users have noted the integrated Dead Letter Queue functionality as a valuable feature that has helped them manage messages effectively and ensure robust message delivery.

User-Friendly Pub/Sub UI: Reviewers have praised the user-friendly Pub/Sub UI, especially its integration with BigQuery and Cloud Storage. The seamless interface has made it convenient for users to work across different platforms effortlessly.

Google Cloud Pub/Sub Reviews

8 Reviews

Connect micro services in your platform by using PubSub

Rating: 9 out of 10

Incentivized

February 6, 2026

Use Cases and Deployment Scope

We use Google Cloud Pub/Sub to communicate between micro services. By using a Pub/Sub topic, we can delegate not so time critical tasks to be processed asynchronously by another micro service.

Using a BigQuery subscription, we can automatically write events sent to a Pub/Sub topic into a BigQuery table.

Pros

Push subscription that can trigger a HTTP endpoint
Supports retries
BigQuery subscription for writing into a BigQuery table

Cons

Allow write and read of messages more than 10 MB
Support rate at which HTTP endpoints are triggered to reduce scale requirements on downstream services
Support replay of messages

Likelihood to Recommend

A Google Cloud Pub/Sub topic can be used to delegate not so time critical processing to be done asynchronously in another micro service. Google Cloud Pub/Sub supports a push subscription which can trigger a HTTP endpoint. Use a Google Cloud Pub/Sub BigQuery subscription to write into a BigQuery table. Google Cloud Pub/Sub is not suited when the incoming message traffic is bursty.

Verified User

Team Lead in Engineering (1-10 employees)

Vetted Review

4 years of experience

Google Cloud Pub/Sub, the jewel of streaming data

Rating: 10 out of 10

April 4, 2023

Use Cases and Deployment Scope

We used Google Cloud Pub/Sub to solve ETL/Streaming and real-time processing problems for high volumes of data. We used it either to fill datalakes, process and store in warehouses or data marts and also for processing events, either using JSON or protobuf.

This was integrated for many languages such as python, java, golang and kotlin. We had configured kubernetes auto scaling system based on some Google Cloud Pub/Sub metrics which worked very well. The main observed metrics for alerts and overall health indicator of our systems were both the size of each queue and the oldest message in queue, either indicating a high volume jam or some random specific error for a single message, respectively.

We had to handle idempotency since a duplicated message delivery is a possibility, this was usually paired and a Redis Cache to guarantee idempotency for a reasonable time window.

Pros

Data Streaming
Even Sourcing
Protobuf message format
Scalability
Easy to Use
Observability
Integrated Dead Letter Queue (DLQ) functionality

Cons

Deliver Once (idempotency) - currently in preview
Vendor locked to Google

Likelihood to Recommend

If you want to stream high volumes of data, be it for ETL streaming or event sourcing, Google Cloud Pub/Sub is your go-to tool. It's easy to learn, easy to observe its metrics and scales with ease without additional configuration so if you have more producers of consumers, all you need to do is to deploy on k8s your solutions so that you can perform autoscaling on your pods to adjust to the data volume. The DLQ is also very transparent and easy to configure. Your code will have no logic whatsoever regarding orchestrating pubsub, you just plug and play.

However, if you are not in the Google Cloud Pub/Sub environment, you might have trouble or be most likely unable to use it since I think it's a product of Google Cloud.

Cézar Augusto Nascimento e Silva

Solutions Architect, Tech Lead, Software Engineer in Information Technology at Stilingue (201-500 employees)

Vetted Review

4 years of experience

View profile

Google Pub/Sub review & usage with FinOps

Rating: 8 out of 10

Incentivized

July 19, 2022

Use Cases and Deployment Scope

We mainly use Google Cloud Pub/Sub with cloud functions and google scheduler to handle FinOps subjects. For example :
- Stopping a Google Kubernetes Engine (GKE) using a cloud scheduler that publishes to a pub/sub topic which then triggers a python function that changes GKE configurations.
- Stopping a Google SQL database using Google scheduler and Google Cloud Pub/Sub.

Pros

Pub/Sub UI
Pub/Sub subscriptions & message retrieval.
Integration with BigQuery & Cloud Storage.

Cons

Debugging
Error screening

Likelihood to Recommend

Using Google Cloud Pub/Sub will mainly depend on the cloud platform used. Our client didn't choose GCP for Google Cloud Pub/Sub, if we went with AWS we would be using SNS/SQS (obviously). However, Google Cloud Pub/Sub is a better solution in the GCP services compared to self-managed solutions such as RabbitMQ for instance (it is managed by GCP and integrates with GCP solutions).

Mehdi Bettiche

Senior Consultant in Information Technology at Wavestone (1001-5000 employees)

Vetted Review

1 year of experience

Overview of Google Cloud Pub/Sub

Rating: 9 out of 10

Incentivized

July 14, 2022

Use Cases and Deployment Scope

Fully managed messaging middleware useful for service integration. We have mainly used it for large scale logs from Kubernetes clusters. Pub/Sub proved to be easy to use, with a clear, user-friendly UI, well documented SDK, built-in elasticity and was the foundation for a real time data management system. Overall, very pleased with Google Cloud Pub/Sub.

Pros

Messaging
Scalable
No-ops
Secure

Cons

Only usable within GCP

Likelihood to Recommend

Google Cloud Pub/Sub is ideal for any real-time data project, especially with large datasets in the terabytes per day range. We have used it successfully in a variety of use cases ranging from recommendations engines (where we’d need to ingest in real time people’s clickstream) to more ops related Kubernetes cluster provisioning and monitoring (based on Kubernetes control plane events).

Verified User

Director in Engineering (501-1000 employees)

Vetted Review

5 years of experience

Great Asynchronous Data Messaging Services, Reliable, Scalable and fully managed by Google

Rating: 9 out of 10

Incentivized

May 26, 2021

Use Cases and Deployment Scope

Google [Cloud] Pub/Sub is used for high Volume, high speed data stream from multiple data sources towards a Data Platform. This is setup by Central Data and Analytics team to serve business use cases for most of the departments like Marketing, Product, Sales, Editorial etc. within our organization

Business Problems addressed

Identify Non App users , their inactivity and show such users a personalized promo on the website when they visit
Identify low engaged users overall, ingest their past usage patterns and cluster them in lookalike user segments to show them next best actions
Capture users' behavior and interactions as "Topics" in Pub/Sub and show them next best action as appropriate

Pros

With a pub/sub architecture the consumer is decoupled in time from the publisher i.e. if the consumer goes down, it can replay any events that occurred during its downtime.
It also allows consumer to throttle and batch incoming data providing much needed flexibility while working with multiple types of data sources
A simple and easy to use UI on cloud console for setup and debugging
It enables event-driven architectures and asynchronous parallel processing, while improving performance, reliability and scalability

Cons

It is limited to work with the same platform but with different datasets at the same time, you must request a prior security authentication.
It can sometimes lead to unexpected charges, as Pub/Sub will automatically keep on retrying messages continuously, even if failures are due to permanent code-level issues.
Message re-deliveries don't apply for ingested services like with Python based client. Push messages tried to be delivered immediately and if your service is busy dealing with some other task, it won't be done OR goes into a queue

Likelihood to Recommend

Well Suited for

One Source, multi subscribers scenario, where there is no issue with errors on multiple source datasets and anyone who is subscribed to a Topic receives the messages
The load of the messages are totally comfortable, the workspace inside the platform, the functions of messaging and calls of the properties are easy to use
Reliable and Scalable model for creating and maintaining a big data pipeline

Less Appropriate for:

Ingesting multiple datasets from same data sources at the same time
Many Google Cloud Pub/Sub classes are concrete and not interfaces, making them harder to plan for when writing unit or integration tests

Verified User

Manager in Marketing (1001-5000 employees)

Vetted Review

3 years of experience

Reliable Pub/Sub Vendor

Rating: 10 out of 10

October 26, 2020

Use Cases and Deployment Scope

Google Cloud Pub/Sub is used for processing scheduled tasks, sending notifications to clients and other background job execution. It helps in the point-in-time queue to send notifications to customers. As a team lead, I helped my team to transition from the legacy queue system to the Google Cloud Pub/Sub real-time system to capture Play billing alerts in real time.

Pros

Queue Caching
Notification Service
Background Task

Cons

Priority Queue is a missing feature

Likelihood to Recommend

Every Google Play billing console user who handles subscriptions at scale should definitely adopt pub/sub for seamless processing.

Verified User

Engineer in Engineering (1001-5000 employees)

Vetted Review

2 years of experience

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

Rating: 9 out of 10

Incentivized

December 14, 2019

Use Cases and Deployment Scope

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.

Pros

Highly scalable.
Queues messages for up to 7 days if not acknowledged.

Cons

Would be nice if the queue could be extended beyond 7 days.
We found it a bit tricky replay unacknowledged messages when needed.

Likelihood to Recommend

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.

Eric Mason

Lead Developer in Engineering at SaaSquatch (11-50 employees)

Vetted Review

1 year of experience

Messaging Service is Great for Distributed Systems

Rating: 9 out of 10

Incentivized

October 18, 2019

Use Cases and Deployment Scope

We have a highly distributed system of batch jobs. We use Google Cloud Pub/Sub in order to communicate between our front-end, orchestration software, and VMs running batch workloads. It serves as a key piece under the hood for running jobs for scientists and it allows us to distribute our workloads across specialized VMs.

Pros

A hands-off approach to publishing messages and subscribing to topics.
Easy to use APIs.
Useful, simple UI on cloud console to send messages for debugging, etc.

Cons

I can't think of missing functionality, but added functionality is always nice!

Likelihood to Recommend

Pub/Sub is perfect for all distributed systems. Whether it be services talking to each other, being the middleman between applications and Cloud Functions, or sending messages between standalone VMs that rely on one another, Pub/Sub makes it easy to communicate between pieces. It is ideal as a publication/subscription software as a service.

Cameron Gable

Software Engineer in Research & Development at Serimmune Inc. (11-50 employees)

Vetted Review

2 years of experience

View profile

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Great Asynchronous Data Messaging Services, Reliable, Scalable and fully managed by Google

Rating: 9 out of 10

Incentivized

May 26, 2021

Use Cases and Deployment Scope

Identify Non App users , their inactivity and show such users a personalized promo on the website when they visit
Identify low engaged users overall, ingest their past usage patterns and cluster them in lookalike user segments to show them next best actions
Capture users' behavior and interactions as "Topics" in Pub/Sub and show them next best action as appropriate

Pros

With a pub/sub architecture the consumer is decoupled in time from the publisher i.e. if the consumer goes down, it can replay any events that occurred during its downtime.
It also allows consumer to throttle and batch incoming data providing much needed flexibility while working with multiple types of data sources
A simple and easy to use UI on cloud console for setup and debugging
It enables event-driven architectures and asynchronous parallel processing, while improving performance, reliability and scalability

Cons

It is limited to work with the same platform but with different datasets at the same time, you must request a prior security authentication.
It can sometimes lead to unexpected charges, as Pub/Sub will automatically keep on retrying messages continuously, even if failures are due to permanent code-level issues.
Message re-deliveries don't apply for ingested services like with Python based client. Push messages tried to be delivered immediately and if your service is busy dealing with some other task, it won't be done OR goes into a queue

Likelihood to Recommend

Well Suited for

One Source, multi subscribers scenario, where there is no issue with errors on multiple source datasets and anyone who is subscribed to a Topic receives the messages
The load of the messages are totally comfortable, the workspace inside the platform, the functions of messaging and calls of the properties are easy to use
Reliable and Scalable model for creating and maintaining a big data pipeline

Less Appropriate for:

Ingesting multiple datasets from same data sources at the same time
Many Google Cloud Pub/Sub classes are concrete and not interfaces, making them harder to plan for when writing unit or integration tests

Verified User

Manager in Marketing (1001-5000 employees)

Vetted Review

3 years of experience