[Storage] Implement batch ingestion API for high-volume RDF datasets #615

Summary

Provide an optimized batch ingestion API in core.next.storage to ingest high-volume RDF graphs without memory exhaustion or excessive garbage collection overhead.

Objectives and Technical Scope

1. Batch Ingestion Interface

• Design a high-throughput batch loading contract (addBatch(Iterable<Statement>) / stream consumer) in core.next.storage.api.
• Implement bulk index population that minimizes pointer re-allocations and tree rebalancing overhead.

2. Index Deferral and Rebuilding

• Support temporary index suspension or bulk insertion modes during massive loads, followed by deterministic index finalization.

Acceptance Criteria

[ ] Bulk loading of 100,000+ statements completes without memory exhaustion or GC stalls.
[ ] All index invariants (SPO, POS, OSP) are fully satisfied and consistent post-ingest.
[ ] Memory footprint per statement during batch loading is measurably optimized compared to one-by-one insertion.