Turbopuffer is rebuilding its database engine to stop treating vector indexes as the primary key. The company found that organizing everything around ANN addresses works great for vector search but cripples performance for filtering, full-text search, and aggregations—so they're moving to a new primary index that treats vectors as just another secondary index.

• The current architecture forces document duplication when storing multi-vector representations and cascades full document rewrites whenever the ANN index rebalances, creating massive write amplification that's hitting diminishing returns on throughput tuning.
• Non-vector query plans are constrained to tiny block sizes (100–200 docs) by the ANN index, while modern query engines need thousands of documents per block to vectorize efficiently—full-text search got 10x smaller and 20x faster just by switching to 256-doc blocks.
• Turbopuffer v3 passes all CI tests but shows significant performance regressions; the team is now in the optimization phase and plans to publish benchmarks as they tune the new architecture.