Rumors, opinions, hearsay, facts, version-related benchmarks, some personal experience, etc...

Multiple threads can improve throughput, but there are limitations:

• The throughput upper limit is approximately half of the theoretical limit. (your "percentage") (This is a benchmark based on the multithreading package; I forget the name; that was ten years ago.)
• Multiple threads will compete with each other on mutexes and other necessary locking mechanisms.
• Starting around 5.7, 64 threads is the multi-threading limit for MySQL; beyond this value, throughput will stagnate or even decrease. (Source: Many Oracle benchmarks boast that one version is significantly better than the previous one.) (Meanwhile, per-thread latency is through the roof.)
• If possible, each thread should process data in batches.

Batch processing:

• LOAD DATA is the fastest way to INSERT a large number of rows at once from a single thread. However, if you include the cost of writing the file to LOAD, it may make it slower than a bulk insert.
• BULK INSERT follows. But it's capped at "hundreds" of rows when a certain limit or "diminishing returns" is reached.
• Batch inserts are 10 times faster than inserting one row per INSERT query. Therefore, it (or LOAD DATA) is worth using for high-speed ingestion. (Source: Many different timed tests.)

Data Sources:

• Some data sources must transmit only one row at a time (e.g., sensor data from a vehicle every N seconds). This requires some middle layer to batch process the data.
• Discussion of collecting data: http://mysql.rjweb.org/doc.php /staging_table

What happens after loading the data? Of course, this is not a write-only table.

• Normalization is useful for shrinking the disk footprint; best done in batches. SeeStandardization
• PARTITIONing Rarely useful, except to eventually clear out old data. SeePartition
• Huge "fact" tables are difficult to search; consider building summary data when ingesting: Summary table
• You can even do the above processing and then throw away the original data. It sounds like you might be getting a terabyte of data per day.