Amazon Kinesis vs Google Cloud Dataflow comparison

Amazon Web Services (AWS) and Google are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #2 with an average rating of 7.9, while Google is ranked #8 with an average rating of 7.9. Amazon Web Services (AWS) holds a 9.8% mindshare in SA, compared to Google’s 8.4% mindshare. Additionally, 89% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 90% of Google users who would recommend it.

Amazon Kinesis

Read 27 Amazon Kinesis reviews

7,426 Views
5,574 Comparison Views

89% willing to recommend

Google Cloud Dataflow

Read 10 Google Cloud Dataflow reviews

3,614 Views
3,001 Comparison Views

90% willing to recommend

Amazon Kinesis

Google Cloud Dataflow

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Google Cloud Dataflow and Amazon Kinesis are solutions in data processing and analytics. Dataflow is known for handling batch processing while Kinesis focuses on real-time data analytics and scalability, making Kinesis favorable for real-time capabilities.

Features: Google Cloud Dataflow is geared towards large-scale processing with features like autoscaling, a unified programming model, and comprehensive batch processing. Amazon Kinesis offers real-time data streaming, seamless AWS integration, and robust data analytics options, including advanced data streams and firehose capabilities.

Room for Improvement: Google Cloud Dataflow could improve its real-time processing and AWS integration capabilities. Its cost model might be refined for consistent large-scale operations. Amazon Kinesis could benefit from enhanced user interface features, improved support for diverse programming languages, and more streamlined data storage options.

Ease of Deployment and Customer Service: Google Cloud Dataflow is noted for an easy deployment process and thorough documentation, simplifying user onboarding. Amazon Kinesis offers straightforward deployments with excellent AWS ecosystem integration, providing robust infrastructure support and dedicated customer service.

Pricing and ROI: Google Cloud Dataflow operates on a pay-per-use model, which is effective for variable workloads, offering flexibility. Amazon Kinesis uses a pay-as-you-go model as well, providing a more predictable pricing structure, potentially leading to better ROI in consistent high-volume data environments, despite initial costs.

To learn more, read our detailed Amazon Kinesis vs. Google Cloud Dataflow Report (Updated: January 2025).

Buyer's Guide

Amazon Kinesis vs. Google Cloud Dataflow

January 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Amazon Kinesis

Ranking in Streaming Analytics

2nd

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Google Cloud Dataflow

Ranking in Streaming Analytics

8th

Average Rating

7.8

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2025, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 9.8%, down from 15.3% compared to the previous year. The mindshare of Google Cloud Dataflow is 8.4%, up from 7.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

Rajni Kumar Jha

Senior Software Engineer at JPMorgan Chase & Co.

Used for media streaming and live-streaming data

It is not compulsory to use Amazon Kinesis. If you don't want to use the data streaming, you can use just the Kinesis data firehose. Using the Kinesis data firehose is compulsory because we can't store all chats and recordings in Amazon S3 without it. When a call comes in the Amazon Kinesis instance, it will go to Data Streams if we use it. Otherwise, it will go to the Kinesis data firehose, where we need to define the S3 bucket path, and it will go to Amazon S3. So, without the Kinesis data firehose, we can't store all the chats and recordings in Amazon S3. Using Amazon Kinesis totally depends upon the user's requirements. If you want to use live streaming for the data lake or data analyst team, you need to use Amazon Kinesis. If you don't want to use it, you can directly use the Kinesis data firehose, which will be stored in Amazon S3. Overall, I rate the solution an eight out of ten.

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Tamer Talal

Satellite System Engineer at NARSS

A tool useful for data transmission and data storage that needs to improve its authentication area

The authentication part of the product is an area of concern where improvements are required. For some common users, the solution's authentication part is difficult to use. The scalability of the product is an area of concern where improvements are required. In the future, the product should be made available at a cheaper rate.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The product's initial setup phase is not difficult because we are using the tool on the cloud."

"The most valuable feature is that it has a pretty robust way of capturing things."

"What I like about Amazon Kinesis is that it's very effective for small businesses. It's a well-managed solution with excellent reporting. Amazon Kinesis is also easy to use, and even a novice developer can work with it, versus Apache Kafka, which requires expertise."

"The feature that I've found most valuable is the replay. That is one of the most valuable in our business. We are business-to-business so replay was an important feature - being able to replay for 24 hours. That's an important feature."

"Amazon Kinesis has improved our ROI."

"The solution's technical support is flawless."

"Kinesis is a fully managed program streaming application. You can manage any infrastructure. It is also scalable. Kinesis can handle any amount of data streaming and process data from hundreds, thousands of processes in every source with very low latency."

"One of the best features of Amazon Kinesis is the multi-partition."

More Amazon Kinesis pros

"The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use."

"The best feature of Google Cloud Dataflow is its practical connectedness."

"The support team is good and it's easy to use."

"The product's installation process is easy...The tool's maintenance part is somewhat easy."

"The service is relatively cheap compared to other batch-processing engines."

"The solution allows us to program in any language we desire."

"Google Cloud Dataflow is useful for streaming and data pipelines."

"I don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service."

More Google Cloud Dataflow pros

Cons

"We were charged high costs for the solution’s enhanced fan-out feature."

"There are some kind of hard limits on Amazon Kinesis, and if you hit that, then you will get the throughput exceed error."

"If there were better documentation on optimal sharding strategies then it would be helpful."

"The services which are described in the documentation could use some visual presentation because for someone who is new to the solution the documentation is not easy to follow or beginner friendly and can leave a person feeling helpless."

"Snapshot from the the from the the stream of the data analytic I have already on the cloud, do a snapshot to not to make great or to get the data out size of the web service. But to stop the process and restart a few weeks later when I have more data or more available of the client teams."

"There could be valid data in Kinesis that is not being processed, which affects stability. Although it rarely happens, this issue has been observed in many deployments, making it not completely stable."

"The tool should focus on having an alert system rather than having to use a third-party solution."

"Kinesis can be expensive, especially when dealing with large volumes of data."

More Amazon Kinesis cons

"When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs."

"I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool."

"The deployment time could also be reduced."

"Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job."

"They should do a market survey and then make improvements."

"The authentication part of the product is an area of concern where improvements are required."

"Google Cloud Dataflow should include a little cost optimization."

"The solution's setup process could be more accessible."

More Google Cloud Dataflow cons

Pricing and Cost Advice

"Amazon Kinesis pricing is sometimes reasonable and sometimes could be better, depending on the planning, so it's a five out of ten for me."

"Under $1,000 per month."

"The pricing depends on the use cases and the level of usage. If you wanted to use Kinesis for different use cases, there's definitely a cheaper base cost involved. However, it's not entirely cheap, as different use cases might require different levels of Kinesis usage."

"In general, cloud services are very convenient to use, even if we have to pay a bit more, as we know what we are paying for and can focus on other tasks."

"It was actually a fairly high volume we were spending. We were spending about 150 a month."

"The fee is based on the number of hours the service is running."

"The solution's pricing is fair."

"I rate the product price a five on a scale of one to ten, where one is cheap, and ten is expensive."

More Amazon Kinesis pricing and cost advice

"Google Cloud Dataflow is a cheap solution."

"Google Cloud is slightly cheaper than AWS."

"The solution is not very expensive."

"The tool is cheap."

"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a seven to eight out of ten."

"The solution is cost-effective."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

18%

Manufacturing Company

10%

Retailer

Financial Services Firm

17%

Retailer

13%

Manufacturing Company

12%

Computer Software Company

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Amazon Kinesis?

Amazon Kinesis's main purpose is to provide near real-time data streaming at a consistent 2Mbps rate, which is really impressive.

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What is your experience regarding pricing and costs for Amazon Kinesis?

Amazon Kinesis is moderately priced. In comparison with other competitors, it is fairly priced, however, if they reduced the price a little, it could add more value to customers.

See all answers

What needs improvement with Amazon Kinesis?

I do not see any scope for improvement as it does what it is supposed to do. No changes are required. Since it's predominantly a back-end service, any end-user isn't going to interact with it direc...

See all answers

What do you like most about Google Cloud Dataflow?

The product's installation process is easy...The tool's maintenance part is somewhat easy.

See all answers

What is your experience regarding pricing and costs for Google Cloud Dataflow?

The solution is not very expensive.

See all answers

What needs improvement with Google Cloud Dataflow?

See all answers

Comparisons

Azure Stream Analytics vs Amazon Kinesis

Compared 29% of the time

Confluent vs Amazon Kinesis

Compared 24% of the time

Apache Flink vs Amazon Kinesis

Compared 14% of the time

Amazon MSK vs Amazon Kinesis

Compared 13% of the time

Databricks vs Amazon Kinesis

Compared 4% of the time

More Amazon Kinesis Competitors

Databricks vs Google Cloud Dataflow

Compared 42% of the time

Apache NiFi vs Google Cloud Dataflow

Compared 12% of the time

Amazon MSK vs Google Cloud Dataflow

Compared 11% of the time

Apache Flink vs Google Cloud Dataflow

Compared 9% of the time

Informatica Data Engineering Streaming vs Google Cloud Dataflow

Compared 4% of the time

More Google Cloud Dataflow Competitors

Product Reports

Buyer's Guide

Amazon Kinesis

January 2025

Download Amazon Kinesis product report

Buyer's Guide

Streaming Analytics

January 2025

Download Google Cloud Dataflow product report

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis

Google Dataflow

Learn More

Amazon Web Services (AWS)

Google

Overview

Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.

Google Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

Sample Customers

Zillow, Netflix, Sonos

Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale

Buyer's Guide

Amazon Kinesis vs. Google Cloud Dataflow

January 2025

Free Report: Amazon Kinesis vs. Google Cloud Dataflow

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