Designed for main memory index:

1. Read optimization
2. Write exclusion
3. CPU Cache & Pipeline friendly
4. Saving memory space

Main memory capacities have grown up to a point where most databases fit into RAM. For main-memory database systems, index structure performance is a critical bottleneck. Traditional in-memory data structures like balanced binary search trees are not efficient on modern hardware, because they do not optimally utilize on-CPU caches. Hash tables, also often used for main-memory indexes, are fast but only support point queries.

Adaptive Radix Tree overcomes these shortcomings.

You could find more details in <The Adaptive Radix Tree: ARTful Indexing for Main-Memory Databases>.

What's more, one important invariant of ART is that every insertion/deletion order results in the same tree because there are no re-balancing operations. Which means it's easier to implement thread-safe structure.

It was proposed for the first time in 2010, it's too new for a memory index structure.

There is no mature implementation in present.

Only supports X86-64 which has CMPXCHG16B feature (only early processors laked it):

16bytes value could be accessed atomically.

Go's invalid pointer checking will find the invalid pointer(value). Although we can disable it, it may cause unpredictable collapse.

1. ART index, UncP/aili

2. ART based on <The ART of Practical Synchronization> flode/ARTSynchronized

Thanks for their contribution!