Vector database comparison
Each provider is profiled from its own documentation, with the source recorded against every figure. Dimensions and similarity metrics decide whether an embedding model's output fits at all; hybrid search decides whether keyword relevance survives the move to vectors.
Error tracking and observability
Vector databases
Caching
| Provider | Entry paid plan | Max dimensions | Hybrid search |
|---|---|---|---|
| Elastic Cloud | Elastic Cloud Hosted Standard, cheapest of four subscription tiers: as low as $99 per month for a production config of 120 GB storage across 2 zones. Gold $114, Platinum $131, Enterprise $184 per month on the same config basis. Serverless is metered, no plan fee. | Not documented | Supported — combines vector similarity scores with BM25F text-relevance scores in a single hybrid query. |
| Pinecone | Builder plan: $20/month flat, for solo developers and small teams. Standard plan is usage-based with a $50/month minimum. | Up to 20000 dimensions per dense vector field (minimum 1), per the create-index schema in API version 2026-07. | Supported — combine a keyword signal (BM25 or sparse) with a dense signal at query time, often with reranking. |
| Qdrant | Smallest paid Managed Cloud cluster (1 node, 0.5 vCPU, 2 GiB RAM, 8 GiB disk) on AWS us-east-1: $0.03566/hour, about $26.10/month, per Qdrant's own Cloud pricing calculator. Calculator estimate for AWS us-east-1; VAT excluded and expressly not a binding offer. | Up to 65,535 dimensions for dense vectors | Native hybrid queries combine dense semantic and sparse lexical (BM25) vectors in a single query |
| Redis Cloud | Essentials: from $0.007/hour, $5/month total. 250 MB-100 GB RAM and SSD, single DB. | Not documented | Not documented |
| Turbopuffer | Launch plan: $16/month minimum usage, including all database features. Scale plan: $256/month minimum. Enterprise: $4,096/month or more, plus a 35% usage premium. | 10,752 maximum dimensions for dense vectors; 1,024 maximum dimensions per sparse vector (sparse total dimensions unlimited) | Supported |
| Weaviate | Flex tier starts at $45/month, pay-as-you-go, no commitment. | 65,535 dimensions maximum per embedding vector in Weaviate Database, because the embedding is stored using uint16. Stated for Weaviate Database generally; the FAQ gives no separate Weaviate Cloud cap. | Supported across all plans. |
Which to consider
Teams that need full-text search and observability on the same underlying engine, or that want the option to self-host later — Elastic's dual identity as a search platform and an observability platform is the actual differentiator against single-purpose competitors.
Teams that want a fully managed vector search product with hybrid search and metadata filtering built in, and don't want to operate the underlying index themselves.
Teams that want a choice of similarity metric rather than one fixed default, or that want the option to self-host the same open-source engine the managed cloud runs.
Teams that want Redis from the company that maintains it, with an on-demand hourly Essentials tier cheap enough to run a small production workload without committing to a fixed plan.
Teams that want vector search billed like storage rather than compute — object-storage-backed pricing tends to undercut memory-resident vector databases at rest, especially for large, cold datasets.
Teams that want hybrid search included on every tier without an add-on, or that want an always-free cluster (not a time-limited trial) to build against before committing to a paid plan.
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