Pinecone

Build knowledgeable AI

4.9•67 reviews•

469 followers

Build knowledgeable AI

4.9•67 reviews•

469 followers

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Databases and backend frameworks

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AI Infrastructure Tools

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Cloud Computing Platforms

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AI Databases

A vector database that makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.

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Pinecone Launches

Pinecone Assistant API service for grounded chat and agent-based applications

Launched on January 23rd, 2025

Pinecone Serverless Build remarkable AI applications

Launched on January 17th, 2024

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4.9

Based on 67 reviews

Review Pinecone?

Reviews praise Pinecone’s speed, reliability, and straightforward developer experience—especially for RAG, semantic search, and large-scale workloads. Makers of

Magic Patterns

CustomGPT

, and

Shortwave

highlight smooth serverless operations, low latency, and easy scaling across heavy, real-time use cases like visual search and high-concurrency apps. Users echo the simple API, fast onboarding, strong documentation, and solid performance under load. A minority note the lack of a self-hosted/open-source option. Overall, Pinecone earns high marks for cost-effective scalability and dependable vector search.

+64

Summarized with AI

Pros

scalability (11)

ease of use (8)

high-performance vector database (8)

AI integration (6)

efficient vector search (5)

cost effective (4)

fast performance (4)

serverless architecture (2)

Pros

Cons

Reviews

All Reviews

Most Informative

used this to build

NeuraVid

(144 points)

•3 reviews

We used Pinecone for fast, scalable vector search to power NeuraVid’s AI-driven video retrieval. Unlike traditional databases, Pinecone is optimized for vector searches (ANN - Approximate Nearest Neighbor). As NeuraVid processes huge volumes of video embeddings, Pinecone’s fully managed infrastructure scales automatically, handling billions of vectors efficiently & we don't have to worry about it.

What's great

scalability (11)high-performance vector database (8)fully managed (1)efficient vector search (5)

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23 views10mo ago

used this to build

Glasp AI Clone: Learning Memory

(112 points)

•19 reviews

We use Pinecone as our vector database to power Glasp’s AI Clone and Learning Memory. It’s incredibly fast, scalable, and reliable—perfect for managing embeddings from users’ highlights and notes. It enables real-time search and retrieval, making the AI Clone feel personal and instant. Compared to other options, Pinecone’s performance and ease of integration stood out.

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17 views10mo ago

•3 reviews

What's great

AI integration (6)scalability (11)ease of use (8)

Was using trieve until they were purchased by mintlify. So glad I was "nudged along" to switch. Way more powerful

What needs improvement

Cant say there's much I'd change other than it's a bit complicated at first.

vs Alternatives

I didn't actually start with Pinecone, but I'm so glad that I ended up there.

Ratings

Ease of use

Reliability

Value for money

Customization

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18 views3mo ago

Pinecone

Build knowledgeable AI

Build knowledgeable AI

Have a question about Pinecone? Ask it here and get a real answer.