Pinecone
A managed vector database for semantic search, RAG, recommendations, and AI agent retrieval.
About Pinecone
Pinecone is a fully managed vector database for AI applications that need fast retrieval across large collections of text, images, or other embedded data. Dense, sparse, and full-text indexes run through one API, giving teams a common retrieval layer for semantic search, recommendation systems, retrieval-augmented generation, and agent memory. New writes become searchable immediately. Its serverless architecture uses distributed object storage and scales with demand, so teams do not have to operate vector-search infrastructure themselves. The console covers index management, record browsing, and performance metrics, while APIs and terminal integrations support code-first workflows. Security options include encryption at rest and in transit, API-key roles, user RBAC, private endpoints, customer-managed encryption keys, and SSO. Pricing starts with a free Starter plan. Builder is a flat $20 per month for smaller teams, Standard has a $50 monthly minimum with usage charges above that amount, and Enterprise uses sales-led pricing. This managed approach cuts operational work, though production teams still have to account for usage costs and decide which plan covers their cloud, region, monitoring, support, and access-control needs.
Best for
Best use cases
Use semantic retrieval when keyword matching misses documents that express the same meaning with different wording.
Add current application records to an index when they must become searchable immediately for RAG or agent responses.
Serve similarity-based product recommendations when a catalog is too large for manual relationships or simple rules.
Compare before choosing
The free Starter plan lowers the cost of prototypes, while production tiers introduce flat or minimum monthly charges.
Managed serverless operation removes database maintenance work, but it also ties the retrieval layer to Pinecone APIs and plan limits.
One API covers dense, sparse, and full-text retrieval, reducing the need to operate separate search systems for each strategy.
Features
Semantic search
Search embedded text, images, or other objects by meaning and context.
Retrieval for AI
Supply relevant, freshly indexed knowledge to RAG pipelines and agents.
Recommendation systems
Find similar catalog items for personalized discovery and related-item experiences.
Pros
- The free Starter plan supports prototypes and small applications without a monthly subscription charge.
- Serverless scaling and managed operations reduce the infrastructure work required to run vector search in production.
- Dense, sparse, and full-text indexes share one API, which simplifies mixed retrieval workflows.
Cons
- Builder costs $20 per month, while Standard starts with a $50 monthly minimum before additional usage charges.
- Cloud and region choice, multiple projects, multiple users, and external monitoring require at least the Builder plan.
- Applications depend on Pinecone APIs and service limits, which adds switching work if the retrieval layer later moves elsewhere.
Pricing Plans
Starter
- On-demand Pinecone Database
- Pinecone Inference and Assistant
- Dense, sparse, and full-text indexes
- Console metrics and community support
Builder
- Everything in Starter
- Increased usage limits
- Cloud and region choice
- Multiple projects and users
- Prometheus and Datadog monitoring
Standard
- Designed for production applications
- Usage charges apply above the monthly minimum
- Free trial available
Enterprise
- Sales-led product plan for enterprise requirements
* Pricing information is for reference only. Please refer to the latest announcement on Pinecone's official website.