Do you know about a triple store that performs well under frequent CRUD operations?

I'm working with RDF data in real-world applications that require frequent create, update, and delete operations — classic CRUD behavior. However, I’ve noticed that many triple stores seem heavily optimized for read-heavy, static workloads, and performance degrades significantly when performing a high volume of writes or updates. --- I’m using a triple store (an RDF graph database) because my data is highly connected and changes often. RDF (Resource Description Framework) is a standard model for representing data as triples, simple statements in the form of: subject – predicate – object. It handles flexible structures and complex relationships way better than a traditional db. Plus, it supports reasoning. Something that’s not really feasible with a regular RDBMS. In terms of volume, we’re expecting anywhere between 5,000 to 7,000 transactions per minute, including a mix of reads, inserts, updates, and deletes.