Amazon Kinesis vs. Google Cloud Pub/Sub

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Kinesis
Score 8.0 out of 10
N/A
Amazon Kinesis is a streaming analytics suite for data intake from video or other disparate sources and applying analytics for machine learning (ML) and business intelligence.
$0.01
per GB data ingested / consumed
Google Cloud Pub/Sub
Score 9.1 out of 10
N/A
Google offers Cloud Pub/Sub, a managed message oriented middleware supporting many-to-many asynchronous messaging between applications.N/A
Pricing
Amazon KinesisGoogle Cloud Pub/Sub
Editions & Modules
Amazon Kinesis Video Streams
$0.00850
per GB data ingested / consumed
Amazon Kinesis Data Streams
$0.04
per hour per stream
Amazon Kinesis Data Analytics
$0.11
per hour
Amazon Kinesis Data Firehose
tiered pricing starting at $0.029
per month first 500 TB ingested
No answers on this topic
Offerings
Pricing Offerings
Amazon KinesisGoogle Cloud Pub/Sub
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Amazon KinesisGoogle Cloud Pub/Sub
Considered Both Products
Amazon Kinesis

No answer on this topic

Google Cloud Pub/Sub
Chose Google Cloud Pub/Sub
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 …
Top Pros
Top Cons
Features
Amazon KinesisGoogle Cloud Pub/Sub
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Amazon Kinesis
8.3
2 Ratings
3% above category average
Google Cloud Pub/Sub
-
Ratings
Real-Time Data Analysis10.01 Ratings00 Ratings
Data Ingestion from Multiple Data Sources9.02 Ratings00 Ratings
Low Latency9.02 Ratings00 Ratings
Integrated Development Tools9.02 Ratings00 Ratings
Data wrangling and preparation10.01 Ratings00 Ratings
Linear Scale-Out6.12 Ratings00 Ratings
Data Enrichment5.01 Ratings00 Ratings
Best Alternatives
Amazon KinesisGoogle Cloud Pub/Sub
Small Businesses
IBM Streams
IBM Streams
Score 9.0 out of 10
Amazon SNS
Amazon SNS
Score 8.4 out of 10
Medium-sized Companies
Confluent
Confluent
Score 7.4 out of 10
Apache Kafka
Apache Kafka
Score 8.4 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 8.1 out of 10
Apache Kafka
Apache Kafka
Score 8.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon KinesisGoogle Cloud Pub/Sub
Likelihood to Recommend
9.0
(3 ratings)
9.4
(7 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(1 ratings)
Usability
-
(0 ratings)
10.0
(2 ratings)
Availability
-
(0 ratings)
10.0
(1 ratings)
Performance
-
(0 ratings)
10.0
(1 ratings)
Support Rating
7.1
(2 ratings)
9.8
(3 ratings)
Configurability
-
(0 ratings)
10.0
(1 ratings)
Product Scalability
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
Amazon KinesisGoogle Cloud Pub/Sub
Likelihood to Recommend
Amazon AWS
Amazon Kinesis is a great replacement for Kafka and it works better whenever the components of the solution are AWS based. Best if extended fan-out is not required, but still price-performance ratio is very good for simplifying maintenance.
I would go with a different option if the systems to be connected are legacy, for instance in the case of traditional messaging clients.
Read full review
Google
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.
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Pros
Amazon AWS
  • Processing huge loads of data
  • Integrating well with IoT Platform on Amazon
  • Integration with overall AWS Ecosystem
  • Scalability
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Google
  • 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
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Cons
Amazon AWS
  • Not a queue system, so little visibility into "backlog" if there is any
  • Confusing terminology to make sure events aren't missed
  • Sometimes didn't seem to trigger Lambda functions, or dropped events when a lot came in
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Google
  • Would be nice if the queue could be extended beyond 7 days.
  • We found it a bit tricky replay unacknowledged messages when needed.
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Likelihood to Renew
Amazon AWS
No answers on this topic
Google
It serves all of our purposes in the most transparent way I can imagine, after seeing other message queueing providers, I can only attest to its quality.
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Usability
Amazon AWS
No answers on this topic
Google
It has many libraries in many languages, google provides either good guides or they're AI generated code libraries that are easy to understand. It has very good observability too.
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Reliability and Availability
Amazon AWS
No answers on this topic
Google
I have never faced a single problem in 4 years.
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Performance
Amazon AWS
No answers on this topic
Google
It's very fast, can be even better if you use protobuf.
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Support Rating
Amazon AWS
The documentation was confusing and lacked examples. The streams suddenly stopped working with no explanation and there was no information in the logs. All these were more difficult when dealing with enhanced fan-out. In fact, we were about to abort the usage of Kinesis due to a misunderstanding with enhanced fan-out.
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Google
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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Alternatives Considered
Amazon AWS
The main benefit was around set up - incredibly easy to just start using Kinesis. Kinesis is a real-time data processing platform, while Kafka is more of a message queue system. If you only need a message queue from a limited source, Kafka may do the job. More complex use cases, with low latency, higher volume of data, real time decisions and integration with multiple sources and destination at a decent price, Kinesis is better.
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Google
Having used Amazon Web Services SNS & SQS I can say that even if the latter may offer more features, Google Cloud Pub/Sub is easier to use. On the other hand, usage of SNS & SQS as well as documentation and troubleshooting is easier with the AWS solution. Since we are not using GCP only for Pub/Sub the choice depends on other variables.
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Scalability
Amazon AWS
No answers on this topic
Google
You can just plug in consumers at will and it will respond, there's no need for further configuration or introducing new concepts. You have a queue, if it's slow, you plug in more consumers to process more messages: simple as that.
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Return on Investment
Amazon AWS
  • Caused us to need to re-engineer some basic re-try logic
  • Caused us to drop some content without knowing it
  • Made monitoring much more difficult
  • We eventually switched back to SQS because Kinesis is not the same as a Queue system
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Google
  • Increased Efficiency with reliable and Google managed services up all the time wit Disaster Recovery in place as well
  • Definitely Lower costs being a cloud based solution and easier to setup
  • Faster Project delivery and go to market plan for the business use cases basis this technology at the back end
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ScreenShots