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."Apache Spark provides a very high-quality implementation of distributed data processing."
"Features include machine learning, real time streaming, and data processing."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"Its scalability and speed are very valuable. You can scale it a lot. It is a great technology for big data. It is definitely better than a lot of earlier warehouse or pipeline solutions, such as Informatica. Spark SQL is very compliant with normal SQL that we have been using over the years. This makes it easy to code in Spark. It is just like using normal SQL. You can use the APIs of Spark or you can directly write SQL code and run it. This is something that I feel is useful in Spark."
"The product’s most valuable features are lazy evaluation and workload distribution."
"With Spark, we parallelize our operations, efficiently accessing both historical and real-time data."
"The deployment of the product is easy."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"The most valuable feature is that it scans the cloud system and if they are any security anomalies it triggers an email."
"Thanks to this solution, we do not need to worry about hardware or resource utilization. It saves us time."
"It's a serverless solution which is the best feature. It helps us because it offers free aspects. From the infrastructure perspective, it helps us manage costs. There is no overhead of estimating how much infrastructure we're going to need. We can focus on building the business functionality that we want to build."
"The installation and configuration of the solution is straightforward."
"AWS Lambda is itself serverless, and it is connected to the API gateway, and you can directly call the API through the API gateway and connect through AWS Lambda."
"I have found all of the features valuable. It's an easy and cheap solution."
"The stability is good."
"Some of the most valuable features are that it's easy to install and use. The performance is also good."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"When using Spark, users may need to write their own parallelization logic, which requires additional effort and expertise."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."
"One limitation is that not all machine learning libraries and models support it."
"The solution’s integration with other platforms should be improved."
"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."
"They could improve the issues related to programming language for the platform."
"It could be cheaper."
"There is room for improvement in user-friendliness. When comparing this solution to others it is not as user-friendly."
"It would be ideal if we could use the solution across different platforms."
"The price in general could always be better."
"AWS Lambda needs to improve its stability."
"If you're running a new application with a significant load, you need to be prepared for potential bottlenecks."
"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."
"We face some problems with the event-driven execution model."
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 Apache NiFi, 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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