TIOBE March 2025 Programming Language Rankings: The Dinosaurs Strike Back
The TIOBE March 2025 index reveals a surprising resurgence of legacy "dinosaur" languages like Delphi, Fortran, Ada, and COBOL alongside Python's continued dominance, highlighting how stability, performance, and entrenched enterprise systems drive language popularity trends across various domains.
TIOBE's March 2025 programming language ranking has been released, titled "The dinosaurs strike back!".
Last month, high‑performance languages showed significant gains in the TIOBE index, indicating strong momentum.
New changes this month include the rise of historic "dinosaur‑level" languages such as Delphi/Object Pascal, Fortran, Ada, and COBOL into the top‑20 positions, with Delphi and Fortran challenging the Top 10.
These older languages are regaining ground because of their stability and performance; many critical systems have run for decades and organizations are reluctant to replace them, especially in high‑reliability fields like aerospace and finance.
As the core developers of these legacy systems retire, enterprises prefer to maintain and extend existing codebases rather than risk new language adoption.
Python remains the number‑one language despite having the lowest performance, thanks to its simple syntax, extensive ecosystem (NumPy, Pandas, TensorFlow, PyTorch), and dominance in data analysis, web development, DevOps, web crawling, and machine‑learning projects.
Survey data shows Python usage percentages: 50% for data analysis, 49% for web development, 35% for DevOps/automation, 32% for web crawling, 31% for machine learning, 28% for education, and 26% for software testing.
The top‑10 languages this month are: Python, C++, Java, C, C#, JavaScript, Go, SQL, Visual Basic, and Delphi/Object Pascal.
Historical ranking charts (1988‑2025) and a "celebrity" list (2003‑2024) illustrate long‑term trends.
The TIOBE index is compiled monthly from data on global engineers, courses, and third‑party vendors, reflecting search engine and community activity (Google, Baidu, Wikipedia, etc.).
While the data provides a useful reference for learning and career decisions, each language has its own suitable application scenarios, and the choice should be based on practical needs rather than popularity alone.
Reference link: https://www.tiobe.com/tiobe-index/
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