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AWS Lambda vs Google Cloud Dataflow comparison

 

Comparison Buyer's Guide

Executive Summary

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

AWS Lambda
Average Rating
8.4
Reviews Sentiment
7.5
Number of Reviews
83
Ranking in other categories
Compute Service (1st)
Google Cloud Dataflow
Average Rating
8.0
Reviews Sentiment
7.3
Number of Reviews
11
Ranking in other categories
Streaming Analytics (8th)
 

Mindshare comparison

AWS Lambda and Google Cloud Dataflow aren’t in the same category and serve different purposes. AWS Lambda is designed for Compute Service and holds a mindshare of 20.8%, down 26.3% compared to last year.
Google Cloud Dataflow, on the other hand, focuses on Streaming Analytics, holds 7.7% mindshare, up 6.8% since last year.
Compute Service
Streaming Analytics
 

Featured Reviews

Wai L Lin O - PeerSpot reviewer
A serverless solution with easy integration features
We use AWS Lambda because it provides a solution for our needs without requiring us to manage our infrastructure. With the tool, we only pay for the resources we use. Additionally, it is straightforward to implement and integrates with other services like API Gateway. The tool's serverless nature has had the most significant impact on our workflow. I find it particularly attractive because it eliminates the need for managing servers. In my previous experience, managing upgrades and updates was quite challenging. The solution's integration process with other AWS services was relatively easy. We primarily use AWS services such as EventBridge for scheduling processes and log management.
Jana Polianskaja - PeerSpot reviewer
Build Scalable Data Pipelines with Apache Beam and Google Cloud Dataflow
As a data engineer, I find several features of Google Cloud Dataflow particularly valuable. The ability to test solutions locally using Direct Runner is crucial for development, allowing me to validate pipelines without incurring the costs of full Dataflow jobs. The unified programming model for both batch and streaming processing is exceptional - requiring only minor code adjustments to optimize for either mode. This flexibility extends to language support, with robust implementations in both Java and Python, allowing teams to leverage their existing expertise. The platform's comprehensive monitoring capabilities are another standout feature. The intuitive interface, Grafana integration, and extensive service connectivity make troubleshooting and performance tracking highly efficient. Furthermore, seamless integration with Google Cloud Composer (managed Airflow) enables sophisticated orchestration of data pipelines.

Quotes from Members

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

Pros

"AWS Lambda's best features are log analysis and event triggering and actioning."
"AWS Lambda is itself serverless, and it is connected to the API gateway, and you can directly call the API through the API gateway and connect through AWS Lambda."
"The serverless computing feature eliminates the need to manage servers, provision, or scale."
"This product is easy to use."
"I think the most valuable feature is the agility of the solution."
"AWS Lambda's most valuable feature is serverless architecture."
"Lambda is trigger-based, which means it only activates when accessed, ensuring cost savings."
"The automation feature is valuable."
"The service is relatively cheap compared to other batch-processing engines."
"It is a scalable solution."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"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."
"The solution allows us to program in any language we desire."
"It allows me to test solutions locally using runners like Direct Runner without having to start a Dataflow job, which can be costly."
"I would rate the overall solution a ten out of ten."
"Google Cloud Dataflow is useful for streaming and data pipelines."
 

Cons

"AWS Lambda needs to improve its stability."
"Lamba functions have cold-starts that can cause some delay."
"AWS Lambda has a limitation where the execution time is capped at 15 minutes per task. Increasing this time would allow for handling heavier tasks more efficiently."
"I think that perhaps Lambda could explore its functionality more."
"There is room for improvement in user-friendliness. When comparing this solution to others it is not as user-friendly."
"AWS Lambda could improve by having no-code or low-code options because currently, you need to be able to write code well to use it."
"There are other similar solutions, such as Google Cloud Platform or Microsoft Azure. They might be better for small tasks."
"Lambda's dashboard could be more user-friendly and customizable. I want the dashboard to have more information to quickly identify what functions and events are running. Also, we want to be able to add more trigger points, push notifications, and events."
"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."
"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."
"The deployment time could also be reduced."
"Google Cloud Dataflow should include a little cost optimization."
"The solution's setup process could be more accessible."
"They should do a market survey and then make improvements."
"The technical support has slight room for improvement."
"The authentication part of the product is an area of concern where improvements are required."
 

Pricing and Cost Advice

"We only need to pay for the compute time our code consumes."
"The solution's price is average."
"The price of the solution is reasonable."
"For licensing, we pay a yearly subscription."
"The fees are volume-based."
"I would rate the tool’s pricing a nine out of ten. The solution’s pricing works on a pay-as-you-go basis."
"AWS is slightly more expensive than Azure."
"AWS Lambda's cloud version isn't expensive, and I'd rate its pricing as five out of five."
"Google Cloud is slightly cheaper than AWS."
"The tool is cheap."
"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 not very expensive."
"Google Cloud Dataflow is a cheap solution."
"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
"The solution is cost-effective."
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Top Industries

By visitors reading reviews
Educational Organization
67%
Financial Services Firm
8%
Computer Software Company
4%
Manufacturing Company
3%
Financial Services Firm
17%
Retailer
12%
Manufacturing Company
12%
Computer Software Company
12%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Which is better, AWS Lambda or Batch?
AWS Lambda is a serverless solution. It doesn’t require any infrastructure, which allows for cost savings. There is no setup process to deal with, as the entire solution is in the cloud. If you use...
What do you like most about AWS Lambda?
The tool scales automatically based on the number of incoming requests.
What is your experience regarding pricing and costs for AWS Lambda?
AWS Lambda is cheaper compared to running an instance continuously. You only pay for what you use, making it cost-effective.
What do you like most about Google Cloud Dataflow?
The product's installation process is easy...The tool's maintenance part is somewhat easy.
What needs improvement with Google Cloud Dataflow?
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 p...
 

Also Known As

No data available
Google Dataflow
 

Overview

 

Sample Customers

Netflix
Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale
Find out what your peers are saying about Amazon Web Services (AWS), Apache, Spot by NetApp and others in Compute Service. Updated: January 2025.
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