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Databy Pinecone
Pinecone
$50/mofree tier available
Vector database for AI
Pinecone is a cloud-native vector database designed for AI applications requiring semantic search, knowledge retrieval, and long-term memory. It provides fully managed serverless infrastructure for storing and querying high-dimensional vector embeddings with instant indexing, fast retrieval, and automatic scaling. The platform integrates with LLMs and supports hybrid search, metadata filtering, and real-time upserts to enable production-grade AI workflows without infrastructure management.
Who it's for
developers
Pricing · freemium
checked today| Plan | Price | Includes |
|---|---|---|
| Starter | $0 /mo | 2 GB storage · 5 indexes with 100 namespaces each · 2M write units/month · 1M read units/month · Community support only · Single region (US East 1) |
| Standard | $50 /mo | Pay-as-you-go beyond $50 minimum · $16/M read units, $4/M write units, $0.33/GB storage · Multi-cloud support (AWS, Azure, GCP) · Email support with 1-3 day response · Multiple regions available |
| Enterprise | $500 /mo | $500/month minimum commitment · Pay-as-you-go pricing beyond minimum · 99.95% uptime SLA · Priority support with dedicated Slack channel · Private networking and compliance features · Volume discounts available |
AI-researched pricing — verify on the official site before subscribing.
Use it for
- — Retrieval-Augmented Generation (RAG)
- — AI agent memory and knowledge bases
- — Semantic search and similarity matching
- — Recommendation engines
- — Long-term memory for LLMs
- — Real-time search applications
- — Metadata filtering and hybrid search
Get the most out of it
- 01Start with the free Starter tier to prototype and test retrieval quality before committing to paid plans.
- 02Monitor read unit costs closely; complex queries with metadata filtering can consume 5-10 read units instead of 1, which multiplies costs at scale.
- 03Use compression and optimize embedding dimensions (384 vs 1536) to reduce storage costs, as 1536-dimension embeddings consume 4x more storage.
- 04Enable bulk import credits and annual commitments to earn discounted usage rates on paid tiers.
- 05Use namespaces instead of creating many small indexes for better efficiency and cost optimization.
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