Last month, Rust appeared to be the programming language on the rise in the TIOBE Programming Community Index. However, in November, Go has taken the spotlight. Meanwhile, the top three languages maintained their positions.
According to the updated rankings:
- At number one, Python jumped from 21.9% in October to 22.85% in November.
- In second place, C++ fell from 11.6% in October to 10.64% in November.
- C++ still comfortably holds its spot above Java in third, which fell slightly from 10.51% in October to 9.6%.
The TIOBE Programming Community Index shows trends in programming languages based on search engine volume.
Go hits the JavaScript ceiling
Go has entered and left the top 10 before. But in November 2024, the programming language ascended to number seven, its highest position yet.
“What makes Go unique in the top 10 is that Go programs are fast and easy to deploy while the language is easy to learn,” wrote TIOBE Software CEO Paul Jansen. “Python, for instance, is easy to learn but not fast, and deployment for larger Python programs is fragile due to dependencies on all kind of versioned libraries in the environment.”
Rust, which sits at number 14 on the index and had been rising in popularity for most of 2024, could also be on its way to the top 10, Jansen said. Rust is also faster than Go. However, Jansen explained that Go programs are “much easier to understand” than Rust programs.
“JavaScript is ubiquitous in software development, although for larger JavaScript systems, we see a shift to TypeScript nowadays,” said Jansen. “If annual trends continue this way, Go will bypass JavaScript within 3 years.”
TypeScript, developed by Microsoft, is a language that adds specific attributes to make it easier to use JavaScript to build large-scale applications. TypeScript holds position 48 on the TIOBE Programming Community Index today.
Fortran continues ascent through the top 10
Elsewhere on the TIOBE Index, Fortran rose from 9th place to 8th. The classic language started making waves in May 2024. Its strengths — numerical analysis and computational mathematics — are especially relevant to contemporary AI.
