"Pinecone recently announced the public preview of Dedicated Read Nodes (DRN), a new capacity mode for its vector database designed to deliver predictable performance and cost at scale for high-throughput applications such as billion-vector semantic search, recommendation systems, and mission-critical AI services. This capability builds on Pinecone's existing serverless on-demand model, offering enterprises provisioned hardware for steady high query volumes without the variability inherent in usage-based pricing."
"Dedicated Read Nodes allocate exclusive compute and memory resources for query operations, ensuring data stays warm in memory and on local SSD storage to avoid latency spikes from cold data fetches and shared queues. With hourly per-node pricing rather than per-request billing, DRN aims to make costs more predictable for workloads with sustained traffic, while delivering consistent low-latency performance even under heavy load. Developers interact with DRN using the same Pinecone APIs and SDKs as they would in on-demand mode, preserving existing code and workflows."
"The architecture scales along two dimensions: replicas to increase query throughput and availability, and shards to expand storage capacity as datasets grow. Pinecone handles data movement and capacity adjustments behind the scenes, eliminating manual migrations and allowing organizations to grow with minimal operational overhead. DRN is particularly suited for applications with strict service-level objectives and consistent demand patterns, such as user-facing assistants requiring sub-100-millisecond latency across millions of vectors o"
Pinecone introduced Dedicated Read Nodes (DRN), a provisioned capacity mode for its vector database that targets predictable performance and cost at high throughput. DRN reserves compute and memory for query operations and keeps data warm in memory and on local SSDs to prevent latency spikes. Pricing is hourly per node rather than per request, improving cost predictability for steady workloads. The system scales via replicas for throughput and availability and shards for storage capacity. Pinecone manages data movement and capacity changes automatically. DRN fits use cases with strict SLOs and consistent demand, such as large-scale semantic search and user-facing assistants.
Read at InfoQ
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