--- title: "SurrealDB vs. Vector Databases | Why Surreal" description: "How SurrealDB compares to Pinecone, Chroma, Weaviate, and Qdrant. Native vectors alongside documents, graphs, and structured data in one database." url: https://surrealdb.com/why/vs-vector-databases --- # SurrealDB vs. vector databases Pinecone, Chroma, Weaviate, and Qdrant are built for one thing: vectors. SurrealDB is multi-model - native vectors alongside documents, graphs, and structured data in one database. [Start free with SurrealDB](https://studio.surrealdb.com/current/instances/deploy) [Explore the database](https://surrealdb.com/surrealdb) 1. ![Babcock](https://surrealdb.com/assets/static/babcock.lo4rnVg1.svg) 2. ![ING](https://surrealdb.com/assets/static/ing.X3I6S3_V.svg) 3. ![British Airways](https://surrealdb.com/assets/static/british-airways.KEsZiwV-.svg) 4. ![Nvidia](https://surrealdb.com/assets/static/nvidia.DaIEuMil.svg) 5. ![Apple](https://surrealdb.com/assets/static/apple.D5pq4flY.svg) 6. ![SpaceX](https://surrealdb.com/assets/static/spacex.CQJEk-IL.svg) 7. ![Samsung](https://surrealdb.com/assets/static/samsung.CH-vQgnb.svg) 8. ![adidas](https://surrealdb.com/assets/static/adidas.DdTC5qhk.svg) 9. ![Tencent](https://surrealdb.com/assets/static/tencent.paQmLxyy.svg) 10. ![Alibaba](https://surrealdb.com/assets/static/alibaba.B16idgfM.svg) 11. ![PolyAI](https://surrealdb.com/assets/static/poly-ai.c3w_fAg6.svg) 12. ![Later](https://surrealdb.com/assets/static/later.Ds736jFO.svg) 13. ![Verizon](https://surrealdb.com/assets/static/verizon.BI7CajdX.svg) 14. ![Liberty Mutual](https://surrealdb.com/assets/static/liberty-mutual.B7qOU1pd.svg) 15. ![Walmart](https://surrealdb.com/assets/static/walmart.BjDg_Sr8.svg) 16. ![Carrier](https://surrealdb.com/assets/static/carrier.D21gC6NX.svg) 17. ![Saks Fifth Avenue](https://surrealdb.com/assets/static/saks-fifth-avenue.COIDpLSb.svg) 18. ![San Francisco Compute Company](https://surrealdb.com/assets/static/sfcc.B7jlImq4.svg) 19. ![Shield AI](https://surrealdb.com/assets/static/shield-ai.pINZ0KJr.svg) 20. ![Wix](https://surrealdb.com/assets/static/wix.DvHhmoBi.svg) THE LIMITATION ## Vectors alone are not enough Vector databases store embeddings, but not the entities, relationships, or metadata that give embeddings meaning. No graph traversal, no ACID transactions, no temporal versioning. Context requires more than similarity search. ### No structured data Vector databases store embeddings. They don't store the entities, relationships, or metadata that give embeddings meaning. ### No graph traversal You can't traverse relationships between entities. A user and their purchases live in separate systems - no join, no graph. ### No transactions Updating a vector and its source document requires two systems. No ACID - one can succeed while the other fails. ### No temporal Vector databases don't track how knowledge evolves. No bi-temporal versioning, no historical queries. THE DIFFERENCE ## Vectors as part of the whole Embeddings live alongside their source documents, entities, and relationships. One record, one transaction, one permission model. ### Co-located data Embeddings live alongside their source documents, entities, and relationships. One record, one transaction. ### Hybrid queries Combine vector similarity, graph traversal, full-text search, and structured filters in a single SurrealQL statement. ### ACID Read-think-write loops commit atomically. Update memory and state in one transaction - both succeed or neither does. ### Unified permissions One permission model for documents, graphs, vectors, and memory. RBAC and record-level access in one place. BEYOND VECTORS ## From vector search to structured memory If you are building agent memory, vectors are just one retrieval signal. Agent Memory combines vector similarity with knowledge graphs, entity extraction, temporal fact tracking, and hybrid retrieval - all running on SurrealDB in a single ACID transaction. ### [Knowledge graph](https://surrealdb.com/agent-memory) Entities, relationships, and facts - not just embeddings. Structural context that vector search alone cannot provide. Learn more ### [Hybrid retrieval](https://surrealdb.com/agent-memory) Vector similarity, BM25 full-text, graph traversal, and temporal filtering composed in a single query. Learn more ### [Temporal awareness](https://surrealdb.com/agent-memory) Bi-temporal versioning tracks when facts were observed and when they were valid. No destructive updates. Learn more TRUSTED BY ## Enterprise teams building on SurrealDB From knowledge graphs to AI assistants - how enterprise teams are building on SurrealDB. ![Samsung](https://surrealdb.com/assets/static/4c58b81e7b3c9466.C_Hv0eml.svg) DATABASE ### [Unlocking insights with knowledge graphs](https://surrealdb.com/customer/samsung) Samsung Ads uses SurrealDB to build dynamic, real-time knowledge graphs for smarter campaign execution - collapsing three legacy data stores into one. Read case study ![Verizon](https://surrealdb.com/assets/static/18b99996c689000f.B5PQ-nI9.svg) DATABASE ### [AI assistant empowering 10,000 technicians](https://surrealdb.com/customer/verizon) Verizon uses SurrealDB to power a generative AI assistant for 10,000 field technicians, delivering instant access to documentation, outage updates, and workflows. Read case study ![Tencent](https://surrealdb.com/assets/static/401d8346058682c8.DqM87mst.svg) DATABASE ### [Unified infrastructure monitoring](https://surrealdb.com/customer/tencent) Tencent consolidated nine backend tools into one real-time monitoring platform powered by SurrealDB's multi-model context graph. Read case study ![PolyAI](https://surrealdb.com/assets/static/c5fa07c66cd05131.BnC7wHcc.svg) DATABASE ### [High-performance customer service AI powered by RAG](https://surrealdb.com/customer/polyai) PolyAI connects SurrealDB to Agent Studio for low-latency, customer-controlled RAG across voice AI experiences. Read case study ![Saks Fifth Avenue](https://surrealdb.com/assets/static/saks-fifth-avenue-white.pDJ9HGmf.svg) DATABASE ### [AI-powered personalisation at massive scale](https://surrealdb.com/customer/saks) Saks Fifth Avenue uses SurrealDB's vector search and graph capabilities to deliver real-time, AI-powered personalisation across 5 million luxury customers and 45 million monthly product-recommendation queries. Read case study FREQUENTLY ASKED QUESTIONS ## Vector databases How does SurrealDB's vector search compare to Pinecone or Weaviate? Can I migrate from a vector database to SurrealDB? Do I still need a vector database if I use SurrealDB? GET STARTED ## The multi-model database for AI Documents, graphs, vectors, time-series - unified in one query language, one engine, one transaction. ![Samsung](https://surrealdb.com/assets/static/4c58b81e7b3c9466.C_Hv0eml.svg)![NVIDIA](https://surrealdb.com/assets/static/nvidia.DaIEuMil.svg)![Apple](https://surrealdb.com/assets/static/f7dc2519e0d212bc.Cn8MYAK7.svg)![Verizon](https://surrealdb.com/assets/static/18b99996c689000f.B5PQ-nI9.svg)![Tencent](https://surrealdb.com/assets/static/401d8346058682c8.DqM87mst.svg) SOC 2 Type 2 GDPR Cyber Essentials Plus ISO 27001 [Start free with SurrealDB](https://studio.surrealdb.com/current/instances/deploy) [Explore the database](https://surrealdb.com/surrealdb) ```json {"@context":"https://schema.org","@type":"Organization","name":"SurrealDB","url":"https://surrealdb.com","logo":"https://surrealdb.com/assets/static/logo.BG7_TG2b.svg","description":"SurrealDB is the unified data layer for AI. A multi-model database for documents, graphs, vectors, and time-series.","foundingDate":"2022","hasCertification":[{"@type":"Certification","name":"SOC 2 Type 2"},{"@type":"Certification","name":"GDPR"},{"@type":"Certification","name":"Cyber Essentials Plus"},{"@type":"Certification","name":"ISO 27001"}],"owns":[{"@type":"SoftwareApplication","name":"SurrealDB","url":"https://surrealdb.com/surrealdb"},{"@type":"SoftwareApplication","name":"Agent Memory","url":"https://surrealdb.com/agent-memory"}],"knowsAbout":["multi-model databases","document databases","graph databases","vector search","time-series databases","SurrealQL","Agent Memory","real-time databases","embedded databases","context layer","graph ontology","distributed database","knowledge graphs","distributed transaction protocols","highly-scalable databases"],"sameAs":["https://www.wikidata.org/wiki/Q124316308","https://github.com/surrealdb/surrealdb","https://twitter.com/surrealdb","https://www.youtube.com/@surrealdb","https://www.linkedin.com/company/surrealdb","https://discord.gg/surrealdb","https://www.reddit.com/r/surrealdb","https://www.instagram.com/surrealdb","https://medium.com/surrealdb","https://dev.to/surrealdb"]} ``` ```json {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://surrealdb.com"},{"@type":"ListItem","position":2,"name":"Vs vector databases","item":"https://surrealdb.com/why/vs-vector-databases"}]} ``` ```json {"@context":"https://schema.org","@type":"FAQPage","mainEntity":[{"@type":"Question","name":"How does SurrealDB's vector search compare to Pinecone or Weaviate?","acceptedAnswer":{"@type":"Answer","text":"SurrealDB provides native vector search alongside documents, graphs, full-text search, and time-series in one engine. Pinecone and Weaviate are dedicated vector databases that require separate systems for other data models. SurrealDB eliminates the sync layer between vectors and the rest of your data."}},{"@type":"Question","name":"Can I migrate from a vector database to SurrealDB?","acceptedAnswer":{"@type":"Answer","text":"Yes. SurrealDB supports the same embedding formats and similarity functions. You can import your existing vectors and gain graph traversal, structured queries, and ACID transactions in one system."}},{"@type":"Question","name":"Do I still need a vector database if I use SurrealDB?","acceptedAnswer":{"@type":"Answer","text":"No. SurrealDB provides native vector indexing with HNSW and brute-force search. Vectors are stored alongside their source entities with full ACID guarantees. There is no need for a separate vector store."}}]} ```