We performed a comparison between Apache Spark and AWS Lambda based on real PeerSpot user reviews.
Find out in this report how the two Compute Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of Apache Spark is its ease of use."
"The most valuable feature of Apache Spark is its flexibility."
"It is useful for handling large amounts of data. It is very useful for scientific purposes."
"I feel the streaming is its best feature."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"The scalability has been the most valuable aspect of the solution."
"The deployment of the product is easy."
"One of the key features is that Apache Spark is a distributed computing framework. You can help multiple slaves and distribute the workload between them."
"The initial setup of AWS Lambda is very straightforward and quick."
"This product is easy to use."
"The feature I found most valuable about Lambda is the fact that it's serverless."
"AWS Lambda's most valuable feature is serverless architecture."
"We moved our users into the Amazon Cognito pool, so it helps us to standardize our security practices, approaches, etc. We can customize Lambda for authentication to integrate it with API Gateway and other services."
"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."
"The most valuable feature of this solution is the API Gateway."
"AWS Lambda is a stable solution."
"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."
"Apache Spark can improve the use case scenarios from the website. There is not any information on how you can use the solution across the relational databases toward multiple databases."
"There were some problems related to the product's compatibility with a few Python libraries."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing."
"The initial setup was not easy."
"The graphical user interface (UI) could be a bit more clear. It's very hard to figure out the execution logs and understand how long it takes to send everything. If an execution is lost, it's not so easy to understand why or where it went. I have to manually drill down on the data processes which takes a lot of time. Maybe there could be like a metrics monitor, or maybe the whole log analysis could be improved to make it easier to understand and navigate."
"I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it."
"AWS Lambda needs to improve its stability."
"My opinion is that the integration could be improved in this solution. We have had some difficulties integrating the EC2 module, but we found a solution for that by ourselves."
"I would like to see the five zero four AWS Lambda invocation fixed. This is basically a time-out error."
"The metrics and reporting for this solution could be improved."
"The setup was pretty complex because there were many steps. For me, it was complex because I was somewhat new at it. It could be easier for someone who has done it a bunch of times. I just found that it was a very dense user experience. There's a lot going on during setup."
"The runtime for the solution can be improved."
"They should work on the solution's stability and pricing."
"I wish to see better execution time in the next release."
Apache Spark is ranked 5th in Compute Service with 60 reviews while AWS Lambda is ranked 1st in Compute Service with 70 reviews. Apache Spark is rated 8.4, while AWS Lambda is rated 8.6. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of AWS Lambda writes "An easily scalable solution with a variety of use cases and valuable event-based triggers". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Azure Stream Analytics, whereas AWS Lambda is most compared with AWS Batch, Amazon EC2 Auto Scaling, Apache NiFi, AWS Fargate and Google Cloud Dataflow. See our AWS Lambda vs. Apache Spark report.
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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.
