Top databases in 2017: Trends for SQL, NoSQL, Big Data, Fast Data
What are the top trends in databases in 2017? What are the hottest data processing technologies and which ones have been left out? The answer lies in our annual JAXenter survey. Eager to see the results? Then let’s waste no more time.
What are the most in demand tools for data storage and processing this year? You know the drill: we asked you to assess the relevance of a collection of database-related topics and you delivered.
We’ve come a long way from our first evaluation of the annual JAXenter survey. We started out with the top programming languages, we showed you the hottest frameworks, the most popular tools and the cloud platforms everyone is using these days. Last week we revealed the most popular architecture trends so it’s only fair that we focus on the top databases trends now.
Let’s have a look at the trends!
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We started by asking you about your interest in general topics and, according to the results, data processing is a very relevant topic for you this year. As you can see in the figure below, both NoSQL and SQL databases are among respondents’ top preferences.
If we combine the percentage of respondents who found them “interesting” with the percentage of people who find them “very interesting,” then we know who the runner-up is: NoSQL databases occupy the second position with 74,8 percent.
Survey respondents have decided: PostgreSQL is the winner. 25,3 percent found it “very interesting” and 37,7 percent found it “interesting”. In total, PostgreSQL managed to get 63 percent of the respondents excited about the prospect of using it this year.
The runner-up is Elasticsearch with a total of 59 percent. It seems that the student has become the master; although Elasticsearch is based on Lucene, the latter didn’t manage to convince as many respondents to give it a try in 2017. The combination Lucene/Solr only grabbed the attention of 43,8 percent of the respondents — it’s definitely a high score but not necessarily compared to Elasticsearch’s result.
A similar shift can be seen in the case of data processing Apache Spark and Hadoop. Survey respondents’ interest in Hadoop (34,8 percent) stands no chance against people’s interest in Apache Spark (53,3 percent).
