Table of Contents

• Overview
• Construction Benchmarks
  • Construction & Destruction
  • Construction & Insert 1 int & Destruction
• Modifying Benchmarks
  • Insert & Erase 100M int
  • Insert & Access with Varying Probability int
  • Insert & Erase uint64_t
  • Insert & Erase std::string
• Accessing
  • Find 1 – 2000 uint64_t
  • Find 1 – 500k uint64_t
  • Find 1 – 100k std::string
  • Find 1 – 1M std::string 👈
  • Iterating
• Conclusion

Again much like Find 1-2000 size_t, except that this time we use 13 byte strings. Every time we insert 4 strings, 800 lookups are performed. This is repeated until 1 million entries are inserted.

Results

Hashes

In Insert & Erase std::string we have evaluated that robin_hood::hash is fastest for 100 byte strings, and this is also the case in this benchmark. libstdc++-v3s performance is a tad slower, FNV1a is very slow.

Hashmaps

Here the advantage of robin_hood::unordered_node_map becomes even more pronounced. It beats all competitors by a nice margin. Memory usage is the second best, only tsl::sparse_map has lower memory usage.

Chart

Each entry shows average time for a single find and access operation (if found). The final number is average over all entries.

1. blue: 0% find success, 1000 byte size std::string
2. orange: 25% find success, 1000 byte size std::string
3. green: 50% find success, 1000 byte size std::string
4. red: 75% find success, 1000 byte size std::string
5. magenta: 100% find success, 1000 byte size std::string