We performed a comparison between Apache Spark and Spring Boot based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Spring Boot has a slight edge in this comparison due to it being the more user-friendly solution. One area where Apache Spark did come out on top was in the ease of deployment category.
"The deployment of the product is easy."
"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 most valuable feature of Apache Spark is its flexibility."
"One of Apache Spark's most valuable features is that it supports in-memory processing, the execution of jobs compared to traditional tools is very fast."
"The most crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations."
"Spark can handle small to huge data and is suitable for any size of company."
"Apache Spark can do large volume interactive data analysis."
"I found the solution stable. We haven't had any problems with it."
"It is a very scalable solution."
"The solution's framework is stable."
"Spring Boot facilitates the use of Java which is open source. We use Github and other libraries that are available which assist in the building we need to do."
"It's great because it simplifies development. Together with MyBatis they make a beautiful pair for Java development."
"I have found the starter solutions valuable, as well as integration with other products."
"It is a stable solution. Stability-wise, I rate the solution a nine out of ten...The initial setup was not complex and was a simple process."
"Spring Boot's most valuable functionalities include inversion of control, dependency injection, and the ability to gather all services, models, and controllers together for easy connectivity to your REST API, as well as the ability to build a modular response and request system. It seamlessly integrates with various backends, such as SQL, events, and messaging systems, making it a user-friendly and efficient Java tool. Additionally, it functions as a reliable business transaction layer, providing excellent support for front-end and back-end visual tools."
"The solution is easy to use; I primarily employ integrated templates such as the REST template."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"The solution needs to optimize shuffling between workers."
"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 would like to see integration with data science platforms to optimize the processing capability for these tasks."
"Apache Spark's GUI and scalability could be improved."
"At the initial stage, the product provides no container logs to check the activity."
"Spark could be improved by adding support for other open-source storage layers than Delta Lake."
"If you want to create large microservices applications, you need to connect several applications and services to each other. It is very complicated, and Spring Boot does not have an integrated solution for it."
"We'd like them to develop more supporting testing."
"The database connectivity could be better in terms of dealing with multi-tenant systems."
"We have specific algorithms for our Load Balancer or API gateway. So those things, if they could make it more precise, that would be beneficial. Sometimes when we are under pressure or any new person who looks into that stuff, we'll get confused or scared because of some difficulties in understanding Which algorithm needs to be used to implement a Load Balancer. When when we Yeah. Because when we say circuit breaker, we need to use it, and then the user gets a blank circuit breaker. This means we are saying the circuit breaker needs to be moved, and then that circuit breaker needs to be elaborated more. What type of algorithm should I do, and what exactly do I need to get done so that this circuit breaker can help me to resolve my issue? Because, you know, because if you go for the circuit breaker, it will ask to open the new tab, you know, since it will check. If the service is not responding, it will wait and go for another connection. So in similar words, if they can explain it a bit more, that will be helpful. Everyone could do their own Google stuff, and they will get it, but they need help understanding how this could help them to resolve the issue. It will be good if Spring Boot provides information about real-time use cases."
"The cloud packaging is not very straightforward."
"The tool's documentation could be improved, especially by tying it back to frequently asked questions and issues users have. A feedback loop in which the documentation targets the most commonly asked user questions would make using the solution easier. Essentially, I want a more user-centered approach to documentation rather than a purely technical focus."
"When the dependencies within those starter packages clash, mismatch or have a hazard, it is hard to solve the issue."
"The current state of Spring Boot's cloud layer requires further development, especially for collecting Java functions for cloud platforms like GCP Cloudground. Having to write every single API request in a single class can be a cumbersome and time-consuming task that is not ideal for Java developers. Additionally, having all API calls in one class and making it the main class presents problems with package visibility. Therefore, there is much room for improvement in the Spring Cloud area."
Apache Spark is ranked 2nd in Java Frameworks with 60 reviews while Spring Boot is ranked 1st in Java Frameworks with 38 reviews. Apache Spark is rated 8.4, while Spring Boot is rated 8.4. 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 Spring Boot writes "It's highly scalable, secure, and provides all the enhanced tools I need. ". Apache Spark is most compared with AWS Batch, Spark SQL, SAP HANA, Cloudera Distribution for Hadoop and AWS Lambda, whereas Spring Boot is most compared with Jakarta EE, Open Liberty, Eclipse MicroProfile, Vert.x and Oracle Application Development Framework. See our Apache Spark vs. Spring Boot report.
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