Scalability and performance are very different. Opting for a performant but not scalable solution is basically an acknowledgement that: - The project will onl

Scalability and performance are very different. Opting for a performant but not scalable solution is basically an acknowledgement that: - The project will only succeed up to a certain point. - After the initial launch, no further changes will be made to the project since new additions are likely to cost performance and lower the upper bound on how many users the system can support. Not many projects are willing to accept either of these premises. Nobody wants to set an upper bound on their success. Also, it should be noted that no language is 'much faster' than any other language. Benchmarks which compare the basic operations across multiple languages rarely find more than 50% performance difference. The more significant performance differences are usually caused by implementation differences in more advanced operations and in any given language, different libraries can offer different performance characteristics so it's not fair to say that a language is slow because some of its default advanced operations are slow. Usually, performance problems come down to people not choosing the best abstract data type for the problem. Some kinds of problems would perform better with linked list, others perform better with arrays or maps or binary trees. Time complexity of any given algorithm is way more significant than the baseline performance of the underlying language.