This time around, it seems the Julia programming language is creeping ever closer to TIOBE’s top 20 languages. Utilized in data analytics and scientific computation, Julia clearly has its adherents, who often cite its speed and other features as good reasons to learn it.
“Julia beats Matlab because it is much more modern and it can be used free of charge,” reads TIOBE’s note accompanying the latest data. “Furthermore, Julia beats Python and R because it is much faster. Since there is a huge demand in the number crunching and modeling field, Julia has a serious chance to enter the top 20 in the near future. Note that the language Rust has also been knocking on the top 20 door for quite some time, but did not succeed so far. Time will tell whether Julia will endure the same fate.”
To generate its monthly rankings, TIOBE leverages data from a variety of aggregators and search engines, including Google, Wikipedia, YouTube, and Amazon. For a language to rank, it must be Turing complete, have its own Wikipedia entry, and earn more than 5,000 hits for +”<language> programming” on Google. While that’s not the most scientific method of determining a language’s “popularity,” it’s a good way to measure which ones are building (or maintaining) some momentum among technologists.
Created at MIT in 2012, Julia hit its version 1.0 milestone in 2018. “The release of Julia 1.0 signals that Julia is now ready to change the technical world by combining the high-level productivity and ease of use of Python and R with the lightning-fast speed of C++,” MIT professor Alan Edelman told MIT’s news portal at the time. Companies ranging from Capital One to Disney and Amazon have utilized Julia in data-related operations, but the language still lags the likes of Python when it comes to general adoption. Perhaps that will change in coming years.