Pinecone
Managed-only, zero-ops, strong metadata support. Exceptional query speed and low latency. 2026 shift from per-pod to serverless pricing — favorable for low-volume, risky for high-query enterprise workloads.
Pinecone Serverless prices on storage ($0.33/GB/month) plus read units ($8.25/M) plus write units ($2/M). Low-volume CRM workloads (under 10M vectors, under 1M queries/month) typically land at $200-$800/month, well below the legacy pod model. High-query workloads can flip the equation: 100M queries/month at $8.25/M reads is $825 just on reads. Pinecone Inference now offers integrated embedding generation with text-embedding-3-large and Cohere models, removing one operational hop. SOC 2 Type II, HIPAA BAA, ISO 27001, in-region inference (US, EU, India) all available.
Qdrant
Agent-native retrieval features — relevance feedback (1.17), tiered multitenancy, low-latency filtered search (4ms p50). Self-hosted or cloud. The performance leader for agent memory backends in 2026.
Qdrant 1.17 (Q1 2026) added relevance-feedback hooks, letting agents refine results based on tool output. Tiered multitenancy isolates customer data without separate clusters — critical for multi-tenant CRM SaaS. Filtered search with payload indexing maintains 4-8ms p50 latency at 100M+ vectors, the fastest in the comparison group. Self-hosted deployment via Docker or Helm; Qdrant Cloud offers managed clusters from roughly $50/month for a starter to enterprise scale. Best fit for agent memory, semantic cache, and high-throughput RAG backends.
Weaviate
Best-in-class native hybrid search (vector + BM25 without plugins). Multi-modal support. Flexible setup options. Winner when your use case requires blended keyword + semantic retrieval.
Weaviate’s hybrid search combines BM25 keyword scoring with vector similarity in a single query, configurable per call via the alpha parameter (0 = pure BM25, 1 = pure vector). Multimodal collections support text, image, and audio embeddings in one schema. Generative search modules call OpenAI, Cohere, or local models inline, returning generated answers alongside retrieved chunks. Weaviate Cloud offers serverless or dedicated tiers; self-hosted via Docker/Kubernetes. Strongest fit for product search, knowledge-base RAG where keyword exact-match still matters (model numbers, SKUs, error codes), and multimodal CRM workloads.
Practitioner Heuristic
Operational simplicity matters most? Pinecone. Raw performance at scale? Qdrant. Native hybrid search? Weaviate. Budget-constrained Postgres shop? pgvector. Billion-scale? Milvus. Don’t overthink — most orgs never outgrow option #1.
Decision tree. Below 10M vectors and your team is small: Pinecone Serverless. Self-hosting required for compliance and you have ops capacity: Qdrant. Hybrid search central to relevance: Weaviate. Already running Postgres and want to start small: pgvector or pgvectorscale. Beyond 1B vectors with extreme throughput: Milvus or self-hosted Qdrant. The biggest practitioner mistake is over-engineering for scale you’ll never reach — Pinecone or pgvector is right for the first year of most CRM AI projects.
Cost Considerations
Worked example for 50M vectors with 5M queries/month. Pinecone Serverless: roughly $1,500-$2,500/month all-in. Qdrant Cloud (3-node cluster): $1,200-$2,000/month. Weaviate Cloud (Standard): $1,500-$2,800/month. Self-hosted Qdrant on AWS (3x m6i.2xlarge + EBS): $900-$1,400/month plus operational overhead. Self-hosted is cheaper at scale only if you have the ops capacity to run it well.
What to Do This Week
Run a 1M-vector load test against your top two candidates with your actual embedding dimension and filter patterns; benchmarks on someone else’s workload don’t predict yours.
