Pinecone stores vectors.
Vecstore delivers search.
Pinecone is a vector index. You bring the embeddings, the database, and the pipeline. Vecstore is a search API. You bring your data. We handle the rest.
Try Vecstore FreePinecone is the engine. You still need to build the car.
Pinecone stack
6 services
to get search working
Embedding API
$50–500/mo
Primary database
$50–300/mo
Sync pipeline
Engineering time
GPU servers
$2–10K/mo
Model management
Engineering time
Query resolution
Added latency
Estimated total at 1M searches/mo
$3,880+ /mo
Vecstore
1 service
to get search working
Embedding API
Included
Primary database
Included
Sync pipeline
Not needed
GPU servers
Not needed
Model management
Handled
Query resolution
Full records
Total at 1M searches/mo
$750 /mo
Only in Vecstore
Things Pinecone can't do.
Pinecone stores and queries vectors. That's it. Everything below requires you to build or buy separately.
Image search
Reverse image, text-to-image, face search, and OCR. No CLIP model to run.
Semantic text search
Send raw text, get results ranked by meaning. No embedding step.
Multilingual search
100+ languages from a single index. No model selection required.
Hybrid search
Keyword precision + semantic understanding in one API call.
NSFW detection
52 categories of content moderation. One endpoint.
Face search
Upload a face, find every match. Vectors only stored, not images.
Side by side
| Vecstore | Pinecone | |
|---|---|---|
| What it is | Search API | Vector index |
| Embedding generation | Built in | Bring your own |
| Data storage | Built in | Separate database required |
| Image search | Native (reverse, text-to-image, face, OCR) | Not available |
| Text search | Semantic + hybrid | Vector similarity only |
| Multilingual | 100+ languages, one index | Depends on your model |
| NSFW detection | 52 categories | Not available |
| Data sync | Not needed | Your responsibility |
| Metadata limit | None | 40KB per vector |
| Query result | Full records | Vector IDs + limited metadata |
| Setup time | Minutes | Days to weeks (with pipeline) |
| Minimum cost | Free tier | $50/mo (Standard) |
Pick the right tool
Pinecone is a solid product for what it does. These tools solve different problems for different teams.
Choose Pinecone when
Custom ML pipelines
Your team needs control over embedding models and fine-tuning
RAG for LLMs
You need tight control over chunking, dimensions, and retrieval scoring
Research and experimentation
You are testing different models and building novel retrieval systems
Choose Vecstore when
Product search
Your users search by describing what they want, not by typing exact terms
Image search
You need reverse image, text-to-image, face search, or OCR without running models
Ship fast, stay fast
Search is a feature in your product, not the product itself. No ML team needed.
With Pinecone, you build the search. With Vecstore, you use it.
Pinecone: search one item
// 1. Generate embedding const embedding = await openai.embeddings .create({ model: 'text-embedding-3-small', input: query }); // 2. Query Pinecone const results = await index.query({ vector: embedding.data[0].embedding, topK: 10 }); // 3. Fetch actual records const ids = results.matches.map(m => m.id); const records = await db.query( 'SELECT * FROM items WHERE id = ANY($1)', [ids] );
3 services. 3 API calls. You manage sync.
Vecstore: search one item
const results = await fetch( `https://api.vecstore.app/databases/${dbId}/search`, { method: 'POST', headers: { 'X-API-Key': apiKey, 'Content-Type': 'application/json' }, body: JSON.stringify({ query }) } );
1 service. 1 API call. Full records returned.
Common questions
Is Vecstore a vector database?
No. Vecstore is a search API. You send data in and search it. We handle embedding generation, indexing, and retrieval internally. You never touch vectors directly.
Can I bring my own embedding model?
Not currently. Vecstore manages the embedding layer to ensure consistent quality and handle model upgrades automatically. If you need control over the embedding model, Pinecone or an open-source vector DB is a better fit.
What about vendor lock-in?
Both are managed services, so you are trusting a vendor either way. The difference is that with Vecstore your data and search live in one place. With Pinecone, your data is in your database, vectors in Pinecone, and an embedding pipeline connects them. Migrating away from Vecstore means swapping one API. Migrating away from Pinecone means re-architecting your search stack.
What if I need Pinecone for RAG and Vecstore for search?
That works. They solve different problems. Use Pinecone for your LLM retrieval pipeline where you need custom embedding control, and Vecstore for user-facing search where you need it to just work.
How does pricing compare?
Pinecone Standard starts at $50/month, but you also pay for your embedding API, primary database, and sync infrastructure. Vecstore starts with a free tier and charges $1.60 per 1K operations. One bill, one service.
Stop building search infrastructure. Start searching.
1M+ searches powered by Vecstore this year
25 Free credits. No credit card required.