VDBBench Leaderboards
cost (e.g..turbopuffer vs. Zilliz vs. Pinecone
Last checked:
What is VDBBench Leaderboards?
A vector database benchmarking leaderboard that compares performance, cost-efficiency, and latency metrics across cloud vector database solutions including Zilliz Cloud, Pinecone, and Turbopuffer. Provides transparent performance data on QPS, P99 latency, recall accuracy, and cold-start behavior across single-tenant and multi-tenant workloads.
VDBBench Leaderboards pricing
Pricing model: Freemium
VDBBench Leaderboards pros
- Comprehensive multi-dimensional benchmarking covering cost, latency, throughput, and recall accuracy
- Side-by-side comparison of competing products with measurable metrics (P99 latency, QPS, recall@10)
- Real-world scenarios including cold-start performance and continuous ingestion with search freshness
- Transparent methodology using publicly available datasets (LAION 100M, Cohere 10M) on AWS us-west-2
VDBBench Leaderboards cons
- Limited to specific vector datasets that may not represent all production use cases
- Only includes select vector database products; new solutions not immediately benchmarked
- Potential bias due to Zilliz hosting and competing with some benchmarked solutions
Frequently asked questions about VDBBench Leaderboards
Which vector databases are compared?
Zilliz Cloud (Capacity 12CU/32CU and Tiered 4CU), Pinecone Serverless, and Turbopuffer (including Pinned variant)
What are the main performance metrics?
Cost per QPS, P99 latency, maximum concurrent QPS, recall@10 accuracy, cold/warm latency ratios, and ingestion-to-search time
What datasets are used for benchmarking?
LAION 100M (100M 768-dimensional dense vectors) for single-tenant and Cohere Large 10M split across 1000 tenants for multi-tenant scenarios
Where are benchmarks conducted?
AWS us-west-2 region with costs based on each product's regional pricing