
Web search API and crawler built for AI agents
MyScale: SQL-compatible vector database combining relational queries with similarity search, ideal for complex relational data workflows. MyScale records 19,350 monthly visits with +21.3% month-over-month growth and Contact for Pricing, Free pricing. Pinecone records 286,732 monthly visits with -31% growth and Freemium, Paid, Contact for Pricing pricing.
SQL-native vector database for production GenAI applications
| Dimension / Metric | ||
|---|---|---|
| Official Domain | myscale.com | pinecone.io |
| Pricing Model | Contact for Pricing, Free | Freemium, Paid, Contact for Pricing |
| Monthly Visits | 19.35K (19,350) | 286.73K (286,732) |
| MoM Traffic Delta | +3.4K (+21.3%) | -128.88K (-31%) |
| Primary Market & Share | 🇺🇸 United States (33.2%) | 🇺🇸 United States (30.2%) |
| Direct Visits / mo | 7.73K | 118.64K |
| User Rating | 4.6 | 4.8 |
| Supported Platforms | Website | Website |
SQL-native vector database for production GenAI applications
Run vector search, text search, filtered search and complex SQL-vector join queries using ordinary SQL syntax, indexes created with a single ALTER TABLE statement.
A purpose-built index engine marketed as delivering around 3x the speed and 3x the savings versus specialised vector databases, with faster ingestion and index building.
Combine vector similarity with BM25 full-text search and metadata filtering to improve retrieval quality and grounding in retrieval-augmented generation pipelines.
A fully managed offering with integrations across popular languages, frameworks and LLM tooling, including observability for AI applications.
The managed vector database and knowledge engine for production AI
Store and query vector embeddings with automatic indexing that requires no manual tuning or algorithm selection.
Writes are acknowledged in under 100ms and become searchable within seconds, while all data is searched in parallel so speed holds at scale.
Connect agents to Pinecone through plugins for Claude Code, Cursor, Copilot, Codex, Gemini CLI, MCP, or a direct REST API with one key.
Serve compiled, governed enterprise knowledge to agents through a single query, cutting token usage and latency versus multi-step RAG loops.

Web search API and crawler built for AI agents

Search and inference APIs that give AI models real-time web data
AI search and retrieval platform for modern apps and commerce
The data, evaluations and systems behind AI that has to be right.

SpecialistSearch foundation built from embeddings, rerankers, and reader APIs
SpecialistSearch foundation built from embeddings, rerankers, and reader APIs

SpecialistVector-graph memory API designed for persistent AI agent context, offering higher-level agent memory features than Pinecone.
SpecialistVector-graph memory API designed for persistent AI agent context, offering higher-level agent memory features than Pinecone.

SpecialistLightning-fast open-source search engine optimized for keyword and text retrieval, but less tailored for dense vector embeddings.
SpecialistLightning-fast open-source search engine optimized for keyword and text retrieval, but less tailored for dense vector embeddings.

Fully managed Milvus vector database built for massive enterprise scale, offering deeper SQL support than Pinecone.
Fully managed Milvus vector database built for massive enterprise scale, offering deeper SQL support than Pinecone.
Free / Open-sourceOpen-source vector database supporting self-hosting and hybrid search, but requires more infrastructure management than Pinecone.
Free / Open-sourceOpen-source vector database supporting self-hosting and hybrid search, but requires more infrastructure management than Pinecone.

Free / Open-sourceGraph database built on object storage for agent memory and context
Free / Open-sourceGraph database built on object storage for agent memory and context

SpecialistRelevance engine combining vector search with behavioral machine learning models, optimized for recommendation systems rather than raw retrieval.
SpecialistRelevance engine combining vector search with behavioral machine learning models, optimized for recommendation systems rather than raw retrieval.

SpecialistManaged RAG API that handles end-to-end document ingestion and parsing, whereas Pinecone focuses purely on vector storage.
SpecialistManaged RAG API that handles end-to-end document ingestion and parsing, whereas Pinecone focuses purely on vector storage.