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."The cool thing about AWS Lambda is that AWS does all the management. For compression, it is all about making the data small and then making it regular size again. We have an encode function and a decode function. AWS Lambda schedules each of those for us. It has a load balancer and all the fancy stuff, depending on the demand. The most valuable part of AWS Lambda is that I only need to write the software. I need to write two functions, and my cloud developer turns them into two AWS Lambda instances. That's it."
"The most valuable features are event-based triggers. They're really good for a reactive style when you want things to happen as soon as something else happens."
"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 feature I found most valuable about Lambda is the fact that it's serverless."
"The solution runs on the latest cloud technology so it is easy to deploy cloud-native projects."
"It's also suitable for companies of any size. For example, we're a large enterprise, and we've used Lambda without any problems in the last 10 months."
"I like that it's easy to use and maintain. Lambda is good and supports different platforms, so you don't need to worry about language or maintenance."
"The support from AWS Lambda is very good, they are responsive."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"It is a scalable solution."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The service is relatively cheap compared to other batch-processing engines."
"The support team is good and it's easy to use."
"The solution allows us to program in any language we desire."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"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."
"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."
"Another challenge I've noticed is that there is a limit to the environment variables such as the 4 KB limit. Although, the advice is to use parameters or other things to store the details when the limit has exceeded the data, this adds additional intensity to the application. If the size limits for environment variables can be revealed, it would be helpful. Even if we have to pay for it, at least we would know that we are not dealing with latency. So, I would like to see the size of the environment variables increased."
"One area of improvement is to include support for more programming languages. AWS Lambda does not support a lot of programming languages. You have to write the Lambda functions in a certain programming language. We are using C++. My developer knows a couple of other languages. Python is his favorite language, but Python is not supported in AWS Lambda."
"Memory limitation is one of the weaknesses of AWS Lambda and as a result, we have to use several Lambda, instead of just one. Recently, I met with an Amazon employee, who is responsible for Lambda as a product. It appears Amazon has some plans with Lambda, so I don’t have to add something to the additional features."
"The deployment process is a bit complex, so it could be simplified to make it easier for beginners to deploy."
"The running time of AWS Lambda runs fine. It takes around five minutes but it would be great if that time could be extended."
"I would like the layers to have a bigger volume. I would like to be able to add more. I don't want to be limited by the layer."
"The support team does not know how to implement and build the solution."
"Google Cloud Dataflow should include a little cost optimization."
"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 solution's setup process could be more accessible."
"The authentication part of the product is an area of concern where improvements are required."
"They should do a market survey and then make improvements."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"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."
"The technical support has slight room for improvement."
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.
