Most Java developers know String.intern() exists.
Far fewer think about what actually happens when millions of duplicate or unique strings start flowing through a production JVM.
This visual breaks down:
• how the String Pool works inside the heap

• why literals and new String() behave differently

• when intern() can save memory

• why == and .equals() are fundamentally different

• how excessive interning can increase memory pressure

• where UseStringDeduplication and StringTableSize fit in modern JVM tuning

The important takeaway:
Interning is powerful when the value space is bounded and repetitive. It becomes dangerous when applied blindly to high-cardinality data.
For architects and senior Java engineers, this is one of those JVM details that looks small in code but can have system-wide consequences in production.

Java #JVM #Java25 #SoftwareArchitecture #PerformanceEngineering #MemoryManagement #BackendEngineering #DistributedSystems