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For the question of what Java developers do on the back end, this article introduces the corresponding analysis and solutions in detail, hoping to help more partners who want to solve this problem to find a simpler and easier way.

For this year's DZone Database Guide, we surveyed software professionals from across the IT industry. We received 1202 responses, with a completion rate of 64%. Based on these figures, we calculated a margin of error of 3%. In this article, we will discuss the continued growth of Node.js in the Web developer community and the most popular back-end language, Java.

The rise of Node.js

Ninety percent of respondents said that using JavaScript; on the client side, as we discussed in the previous article, is expected. Interestingly, 41% of respondents used JavaScript on the server side, while 36% of respondents used JavaScript to locate the server side in our 2017 DZoneWeb and Mobile Development Guide. The high adoption rate of the back-end JavaScript is related to the increase in Node.js runtime usage. In this year's survey, 42% of respondents said their organization uses the Node.js ecosystem. This is up from 35 per cent in 2017 and almost reflects the growth rate of server-side JavaScript over the past year.

Of the respondents who used the Node.js ecosystem, 54% used full-stack development projects and 40% used back-end development projects. When we associate data from respondents working in the Node.js ecosystem with data from the database we use for Web applications, non-relational (or NoSQL) databases have a higher adoption rate among Node.js developers. For respondents whose organizations use Node.js, 56% use MongoDB. For those who use the Java ecosystem for reporting, 43% use MongoDB; among Python ecosystem users, 49% use MongoDB; to use C# ecosystem adopters, and 37% choose MongoDB as their database. Node developers have a higher adoption rate of MongoDB than people working in other back-end environments such as Java,Python and C#, probably due to the asynchronism of the two technologies. In addition, the source. Mongoose uses the JavaScript language, thus allowing Node.js developers to write database logic in the same language as their application logic.

Server-side operation

The back end of the application is a complex place, full of API and database calls, logic, and so on. When we asked respondents how their work was usually divided between the client and the server, 76% told us that the server side exposed that API,70% had server-side execution business logic, and 66% used server-side integrated systems such as databases, message queues and EIS. Despite the growth of Node.js mentioned above, Java is still the main language for performing such operations on the back end. Therefore, for the rest of this section, we will use statistics collected from respondents who built Web applications using Java as a means of comparative analysis.

Although MongoDB is popular among the Node.js developers mentioned above, Web developers who work with Java seem to prefer traditional SQL databases. Of the respondents who told us to build Web applications using Java, 61% used MySQL databases, 46% used OracleDB,45%, used MongoDB,43%, and used PostgreSQL. Comparing these figures with the adoption rates of these databases among the general survey population, Oracle databases are more popular among Java-based Web developers. Among the general survey population, 58% use MySQL,42%, use MongoDB,41%, use PostreSQL,37%, and use OracleDB to meet database needs. One possible explanation for the above-average popularity of OracleDB among Java-based Web developers is that both the Java language and OracleDB are developed by the same organization, so they work well together.

Node.js and Java in the broader developer community

At the end of this article, let's quickly measure the validity of these results by comparing them with data from the larger developer community. First of all, Node.js. In the 2018 StackOverflow Community Survey, Node.js was ranked as the most popular frameowrk, selected by 50% of StackOverflow audiences.

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