Compare Java and Clojure performance with representative workloads, JVM profiling, reflection and boxing checks, allocation analysis, and realistic service-level goals.
Performance comparisons often go wrong when they compare idiomatic Java to un-idiomatic Clojure, or vice versa. The JVM is shared; the question is how your code allocates, dispatches, and uses data structures.
This section helps you compare fairly: define a workload, measure with the right tools, and interpret results with Clojure-specific factors in mind (reflection, boxing, laziness, persistent collection churn).
| Comparison mistake | Better measurement habit |
|---|---|
| Microbenchmarking the wrong path | Use representative input sizes, data shapes, and service boundaries. |
| Ignoring JVM warmup | Account for JIT behavior, allocation, garbage collection, and process startup. |
| Blaming Clojure broadly | Check reflection, boxing, lazy sequence retention, and avoidable intermediate collections. |
| Optimizing without a goal | Compare against latency, throughput, memory, or cost targets that matter to the system. |