Author here,
First of all, hello Hacker News :)
Many of the comments seem to address the design of key hashing. The reason for using hashed keys inside B-tree nodes instead of the string keys directly is threefold:
1) The implementation is simplified.
2) When performing a lookup, it is faster to compare fixed-sized elements than it is to do variable length string comparison.
3) The key length is unlimited.
I should say the documentation page is out of date regarding hash collisions. The format now supports probing thanks to a PR merged yesterday. So inserting colliding keys will actually work.
It is true that databases and other formats do store string keys directly in the nodes. However as a memory format, runtime performance is very important. There is no disk or IO latency to 'hide behind'.
Right now the hash function used is DJB2. It has the interesting property of somewhat preserving the lexicographical ordering of the key names. So hashes for keys like "item_0001", "item_0002" and "item_0003" are actually more likely to also be placed sequentially inside the B-tree nodes. This can be useful when doing a sequential scan on the semantic key names, otherwise you are doing a lot more random access.
Also DJB2 is so simple that it can be calculated entirely by the C preprocessor at compile time, so you are not actually paying the runtime cost of hashing.
We will be doing a lot more testing before DJB2 is finalized in the spec, but might later end up with a 'better' hash function such as XXH32.
Finally, TRON/Lite³ compared to other binary JSON formats (BSON, MsgPack, CBOR, Amazon Ion) is different in that:
1) none of the formats mentioned provide direct zero-copy indexed access to the data
2) none of the formats mentioned allow for partial mutation of the data without rewriting most of the document
This last point 2) is especially significant. For example, JSONB in Postgres is immutable. When replacing or inserting one specific value inside an object or array, with JSONB you will rewrite the entire document as a result of this, even if it is several megabytes large. If you are performing frequent updates inside JSONB documents, this will cause severe write amplification. This is the case for all current Postgres versions.
TRON/Lite³ is designed to blur the line between memory and serialization format.
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