We performed a comparison between AWS Lambda and Google Cloud Dataflow based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Apache, Zadara and others in Compute Service."Lambda is the preferred compute option because of on-demand cost. We don't have to provision any hardware beforehand. We don't have to provision the capacity required for the services because it is serverless."
"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."
"It's a fairly easy solution to learn."
"I think the most valuable feature is the agility of the solution."
"The stability is good."
"The solution is highly scalable."
"AWS Lambda is a stable solution."
"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 support team is good and it's easy to use."
"It is a scalable solution."
"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 product's installation process is easy...The tool's maintenance part is somewhat easy."
"The solution allows us to program in any language we desire."
"The service is relatively cheap compared to other batch-processing engines."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"If you are setting it up on hybrid solution, there is a lot of work that needs to go in."
"Amazon doesn't have enough local support based in our country."
"The security needs to be improved."
"I would like to see more integration with other platforms."
"There were some timeout issues with AWS Lambda as the options provided didn't suit our business cases."
"There's room for improvement in the solution's warm start, which refers to the minimum time it takes to start up a Lambda function if you haven't been running it."
"The metrics and reporting for this solution could be improved."
"We've had to revamp the way that it works due to that 15-minute timeout limitation."
"The authentication part of the product is an area of concern where improvements are required."
"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."
"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."
"They should do a market survey and then make improvements."
"The deployment time could also be reduced."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"The solution's setup process could be more accessible."
AWS Lambda is ranked 1st in Compute Service with 70 reviews while Google Cloud Dataflow is ranked 7th in Streaming Analytics with 10 reviews. AWS Lambda is rated 8.6, while Google Cloud Dataflow is rated 7.8. The top reviewer of AWS Lambda writes "An easily scalable solution with a variety of use cases and valuable event-based triggers". On the other hand, the top reviewer of Google Cloud Dataflow writes "Easy to use for programmers, user-friendly, and scalable". AWS Lambda is most compared with AWS Batch, Amazon EC2 Auto Scaling, Apache NiFi, Apache Spark and Amazon EC2, whereas Google Cloud Dataflow is most compared with Databricks, Apache NiFi, Amazon MSK, Amazon Kinesis and Azure Stream Analytics.
We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.