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Databy Pinecone

Pinecone

Name: Pinecone
Author: 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 Jul 22, 2026

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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