Pinecone vs Meilisearch
Managed vector database for AI — RAG, semantic search, recommendations
vs. Open-source fast search engine — Rust-based, built-in typo tolerance
Pricing tiers
Pinecone
Starter (Free)
2 GB storage, 2M write units/mo, 1M read units/mo, up to 5 indexes. us-east-1 AWS only.
Free
Standard
$50/month minimum. Unlimited storage ($0.33/GB/mo) + writes ($4-4.50/M) + reads ($16-18/M). 20 indexes/project. Multi-region, multi-cloud.
$50/mo
HIPAA Add-on
$190/month add-on for HIPAA-eligible workloads.
$190/mo
Enterprise
$500/month minimum. Higher per-unit rates for dedicated infra + SLA. 200 indexes.
$500/mo
Meilisearch
Self-Hosted (OSS)
MIT license. Single Rust binary. Run anywhere.
$0 base (usage-based)
Cloud — Resource-Based
$23/mo. Pay by CPU/RAM/storage. For high-traffic + vector workloads.
$23/mo
Cloud — Usage-Based
$30/mo. Pre-set search + document limits. 14-day trial. For MVPs/mid-scale.
$30/mo
Cloud — Enterprise
Custom. Self-hosting option + premier support + SLA + compliance.
Custom
Free-tier quotas head-to-head
Comparing starter on Pinecone vs oss on Meilisearch.
| Metric | Pinecone | Meilisearch |
|---|---|---|
| No overlapping quota metrics for these tiers. | ||
Features
Pinecone · 13 features
- Backups + PITR — Automated + manual backups.
- HIPAA Eligible — BAA available via add-on.
- Metadata Filtering — Filter vectors on metadata at query time.
- Monitoring — Metrics endpoint, export to Datadog/Prometheus.
- Namespaces — Multi-tenancy inside an index. Isolate vectors per customer.
- Pinecone Assistant — RAG-as-a-service: upload docs → get a ready chat endpoint.
- Pinecone Inference — Hosted embedding models (multilingual-e5, llama-text-embed-v2, etc.) inside data…
- Pod-Based Indexes — Dedicated pods (p1, s1, p2) for consistent low-latency workloads.
- Private Networking — AWS PrivateLink / VPC peering on Enterprise.
- RBAC — Per-project + per-API-key roles.
- Rerank (Cohere-backed) — Optional reranker on top of vector search.
- Serverless Indexes — Pay per use. No provisioning. Auto-scales.
- Sparse-Dense Vectors — Hybrid search: sparse (keyword) + dense (semantic) together.
Meilisearch · 15 features
- AI-Powered Search (experimental) — Semantic search, embedders.
- API Keys — Scoped keys with action + index + expiration.
- Custom Ranking Rules — Order ranking rules per index.
- Dumps & Snapshots — Full-DB export + snapshot backups.
- Faceted Search — Dynamic facets with counts.
- Federated Search — Multi-index search in one query with normalization.
- Filters — Filter by boolean / range / string conditions.
- Geo Search — Radius + bounding box geo queries.
- instant-meilisearch — Adapter to use Algolia InstantSearch UI libs with Meilisearch.
- Search — Full-text search with typo + prefix handling.
- Sortable Fields — Sort results by any attribute.
- Stop Words — Ignored common words.
- Synonyms — Configure synonym groups per index.
- Tenant Tokens — Short-lived multi-tenant auth tokens.
- Vector / Hybrid Search — Vector search with keyword hybrid mode.
Developer interfaces
| Kind | Pinecone | Meilisearch |
|---|---|---|
| CLI | Pinecone CLI | meilisearch CLI |
| SDK | go-pinecone, @pinecone-database/pinecone, pinecone-java-client, Pinecone.NET, pinecone (Python) | instant-meilisearch (Algolia UI adapter), meilisearch-go, meilisearch-js, meilisearch-php, meilisearch-python, meilisearch-ruby, meilisearch-rust, meilisearch-swift |
| REST | Data Plane (per-index), Pinecone Control Plane | Meilisearch REST API |
| MCP | Pinecone MCP | — |
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