Try our new research platform with insights from 80,000+ expert users

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
8.6
Reviews Sentiment
7.3
Number of Reviews
88
Ranking in other categories
Compute Service (1st)
Google Cloud Dataflow
Average Rating
8.0
Reviews Sentiment
7.3
Number of Reviews
13
Ranking in other categories
Streaming Analytics (7th)
 

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 20.7%, up 19.5% compared to last year.
Google Cloud Dataflow, on the other hand, focuses on Streaming Analytics, holds 6.5% mindshare, down 7.5% since last year.
Compute Service
Streaming Analytics
 

Featured Reviews

Andrew-Wong - PeerSpot reviewer
Convenience in deployment process with room for code preview improvement
Having a better preview would be helpful. Sometimes, if my Lambda code is too big, it can be inconvenient as I'm unable to see my code when it exceeds a certain size. AWS has a limit, like a three-megabyte limit, beyond which I cannot view or edit the code easily.
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

"The solution runs on the latest cloud technology so it is easy to deploy cloud-native projects."
"I like the pay-for-what-you-use feature. This is the main reason why we use AWS Lambda. I don't have to manage servers; I just have to configure Lambda and expose it to an API gateway."
"I have used AWS Lambda for simple messaging for SQS, creating a cron job, and delay messaging."
"AWS Lambda is entirely stable."
"The most valuable feature of AWS Lambda is that you can trigger and run jobs instantly, and after you complete the job, that function is either destroyed or stopped automatedly."
"The automation feature is valuable."
"This product is easy to use."
"Amazon takes care of the scalability. That's the right way. It's automatic and it's fully managed. That's one benefit of Lambda."
"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."
"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."
"Google's support team is good at resolving issues, especially with large data."
"It is a scalable solution."
"I would rate the overall solution a ten out of ten."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"The integration within Google Cloud Platform is very good."
"The service is relatively cheap compared to other batch-processing engines."
 

Cons

"AWS Lambda could be improved by increasing the size of the payload. Also, sometimes Lambda doesn't implement well for bigger solutions."
"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."
"We need to better understand Lambda for different scenarios. We need some joint effort between Amazon and the users to have the users identify how they can really leverage Lambda. It's not about Lambda itself; it's about the practice, the guidance. There needs to be very good documentation. From the user perspective, what exists now is not always enough."
"We've had to revamp the way that it works due to that 15-minute timeout limitation."
"I think that perhaps Lambda could explore its functionality more."
"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."
"I want to see support for longer applications. I need the 15-minute time-out window to improve."
"I would like to see the five zero four AWS Lambda invocation fixed. This is basically a time-out error."
"The authentication part of the product is an area of concern where improvements are required."
"Occasionally, dealing with a huge volume of data causes failure due to array size."
"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."
"I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns."
"The solution's setup process could be more accessible."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"Google Cloud Dataflow should include a little cost optimization."
"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."
 

Pricing and Cost Advice

"We don't need to pay for licensing to use Lambda."
"You're not paying for a server if you're not using it, which is another reason I like it. So, you're not paying if you're not using it. It scales, and you're charged based on usage. It all depends on the use case. Some can be extremely inexpensive if you have very low volume transaction rates. That way, you don't have to fire up and absorb the cost of the servers just sitting there waiting for a transaction to come through. You're only paying when you use it. So, depending upon the use model, Lambda could be highly efficient relative to an EC2 solution. You don't have to have things reallocated."
"AWS Lambda is a cheap solution."
"Price-wise, AWS Lambda is very cheap. It's not free, but it's not that expensive."
"AWS Lambda license is paid on a monthly basis."
"The pricing varies based on the specific solution you're implementing, and in comparison to the value it provides, the overall cost is reasonable."
"AWS Lambda is cost-effective, with a minimal maintenance cost."
"It costs maybe less than $10 per month in my use case."
"Google Cloud Dataflow is a cheap solution."
"The tool is cheap."
"The solution is cost-effective."
"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 not very expensive."
"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."
"Google Cloud is slightly cheaper than AWS."
"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."
report
Use our free recommendation engine to learn which Compute Service solutions are best for your needs.
864,053 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
20%
Computer Software Company
12%
Manufacturing Company
8%
University
6%
Financial Services Firm
17%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
9%
 

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?
The pricing of AWS Lambda is reasonable. It's beneficial and cost-effective for users regardless of the number of instances used.
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 is your experience regarding pricing and costs for Google Cloud Dataflow?
Pricing is normal. It is part of a package received from Google, and they are not charging us too high.
What needs improvement with Google Cloud Dataflow?
I am not sure, as we built only one job, and it is running on a daily basis. Everything else is managed using BigQuery schedulers and Talend. However, occasionally, dealing with a huge volume of da...
 

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, Oracle and others in Compute Service. Updated: July 2025.
864,053 professionals have used our research since 2012.