Compare Spark Software and spring.io 
- Users report that spring.io excels in application deployment with a score of 9.3, highlighting its seamless integration capabilities and robust deployment tools, while Spark, although strong, scores slightly lower at 8.7.
- Reviewers mention that spring.io offers superior development tools, scoring 9.0, which many users appreciate for its comprehensive support for various programming languages, compared to Spark's score of 8.4 in this area.
- G2 users indicate that spring.io shines in database management with a score of 9.3, particularly praising its efficient handling of complex queries, while Spark's score of 8.7 suggests it may not be as robust in this aspect.
- Users on G2 highlight that spring.io's testing capabilities are rated at 9.3, with reviewers noting its extensive testing frameworks, whereas Spark's testing features, rated at 8.1, may not meet the same level of user expectations.
- Reviewers mention that spring.io's quality of support is rated at 8.4, with many users appreciating the responsiveness and helpfulness of the support team, while Spark's support, rated at 7.6, has received mixed reviews regarding response times.
- Users say that spring.io's product direction is rated at 9.1, indicating a strong positive outlook for future updates and features, while Spark's lower score of 7.1 suggests some users are less confident in its ongoing development trajectory.
Spark is one of the useful tools for cloud architecture.
The inefficiency of the product. It is a terrible way to communicate effectively
It really helps me focus on my business features instead of worrying about configuration, boilerplate code and thinks like those. It can be integrated with almost any technology I usually use: relational database, mongoDB, redis, JMS, etc... Moreover...
I have faced a couple of debugging issues. Sometimes fixing failing test cases was difficult to solve. In the long run, you will run into hanging consoles, AspectJ issues, Auto-generated test cases are a mess :( I believe we should generate a normal spring...
Spark is one of the useful tools for cloud architecture.
It really helps me focus on my business features instead of worrying about configuration, boilerplate code and thinks like those. It can be integrated with almost any technology I usually use: relational database, mongoDB, redis, JMS, etc... Moreover...
The inefficiency of the product. It is a terrible way to communicate effectively
I have faced a couple of debugging issues. Sometimes fixing failing test cases was difficult to solve. In the long run, you will run into hanging consoles, AspectJ issues, Auto-generated test cases are a mess :( I believe we should generate a normal spring...
