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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
7.8
Reviews Sentiment
7.3
Number of Reviews
12
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 21.0%, down 24.9% compared to last year.
Google Cloud Dataflow, on the other hand, focuses on Streaming Analytics, holds 7.4% mindshare, up 6.9% 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

"It is my preferred product, as it provides me with source code within the solution."
"The feature I found most valuable about Lambda is the fact that it's serverless."
"The programming language and the integration with other AWS services are the most valuable features."
"AWS Lambda is interlinked with CloudWatch. When we have any errors we can directly go there and check the CloudWatch logs. Additionally, we can run it very fast and we can increase the RAM size and other components."
"The automation feature is valuable."
"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 initial setup is pretty easy."
"Technical support has been great in general."
"I would rate the overall solution a ten out of ten."
"The integration within Google Cloud Platform is very good."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"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."
"The service is relatively cheap compared to other batch-processing engines."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
 

Cons

"The runtime could be improved. There are certain use cases where I need a Lambda function to run longer."
"The 60 seconds limitation with the consumption of the service is really restrictive for a service and the solution can be improved by eliminating that."
"There were some timeout issues with AWS Lambda as the options provided didn't suit our business cases."
"We face some problems with the event-driven execution model."
"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."
"The tool changes its UI every month which is very frustrating for me. I don’t know why AWS keeps changing the UI. They can’t stick to a specific one"
"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."
"Lambda could be improved in the sense that some of the things done with Lambda function take some time. So the performance could be better and faster."
"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."
"Occasionally, dealing with a huge volume of data causes failure due to array size."
"They should do a market survey and then make improvements."
"Google Cloud Dataflow should include a little cost optimization."
"The technical support has slight room for improvement."
"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."
"Promoting the technology more broadly would help increase its adoption."
"The deployment time could also be reduced."
 

Pricing and Cost Advice

"AWS Lambda is inexpensive."
"The solution is free of cost for the first year, and after that, it becomes expensive."
"The pricing is on-demand and based on runs or times that are billed out monthly."
"We don't need to pay for licensing to use Lambda."
"It computes by the cycle, and it's very cheap."
"The fees are volume-based."
"AWS Lambda is not expensive for micro testing but is expensive if used for long deployment or long services."
"The solution is part of the AWS subscription model that is paid annually."
"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
"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."
"The solution is cost-effective."
"Google Cloud is slightly cheaper than AWS."
"The solution is not very expensive."
"Google Cloud Dataflow is a cheap solution."
"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."
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Top Industries

By visitors reading reviews
Educational Organization
68%
Financial Services Firm
8%
Computer Software Company
4%
Manufacturing Company
3%
Financial Services Firm
17%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
11%
 

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 is your experience regarding pricing and costs for Google Cloud Dataflow?
Google Cloud Dataflow costs are primarily driven by compute resources (worker type and count) and data volume. However, other factors like pipeline complexity also contribute significantly to the t...
What needs improvement with Google Cloud Dataflow?
Apache Beam represents a powerful data processing solution that deserves wider recognition in the broader tech community. This technology offers remarkable capabilities for handling data at scale, ...
 

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: February 2025.
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