--- title: "SurrealDB vs. MongoDB | Database comparison" description: "A comparison of SurrealDB and MongoDB features and capabilities." url: https://surrealdb.com/comparison/mongodb --- # SurrealDB vs. MongoDB SurrealDB is a unified, transactional, multi-model database. MongoDB is a document-oriented database with multiple specialised subsystems. [Migrate from MongoDB](https://surrealdb.com/docs/build/migrating/from-other-databases/from-mongodb) [Contact us](https://surrealdb.com/contact) 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) KEY ADVANTAGES ## Why teams choose SurrealDB over MongoDB MongoDB started as a document store and later added search, vector, and limited graph features through separate systems. SurrealDB runs all of this natively in one engine. ### True multi-model engine Document, relational, graph, vector, full-text, temporal, and geospatial access patterns natively in one system. ### Temporal graph querying Time is treated as a first-class constraint within graph traversal. ### Unified indexing No compound multikey limitations across arrays or nested fields. ### ACID without locking Transactions across all data models without global or table-level locking. HOW IT COMPARES ## How SurrealDB and MongoDB differ As apps demand richer models, temporal logic, and AI retrieval, document-centric systems with external subsystems hit composability limits. SurrealDB runs everything in one distributed engine. Feature MongoDB SurrealDB Architecture Document-first with secondary views, full-text search, and vectors requiring duplicated data and separate async pipelines. Unified, distributed multi-model engine. Query execution, indexing, storage, and transactions operate inside a single system. Models Document-first. Graph traversal support is limited. Relational semantics are not planner-driven. Native support for document, relational, graph, key-value, time-series, vector, full-text search, and geospatial. Transactional consistency ACID transactions are limited, costly under contention, and don't extend to search, vectors, or graph traversal. ACID transactions across documents, relational joins, graph traversal, vector search, and full-text search. Query execution Queries split into multiple stages, with $search required first. No unified planner across document, search, vector, and graph operations. Single declarative query language with a unified execution plan. All retrieval primitives are co-planned. Indexing Compound indexes may include only one array field. Deeply nested or multi-array document models cannot be efficiently indexed. Indexing across arrays, nested fields, vectors, and relationships without compound multikey restrictions. Temporal capabilities No temporal graph querying. Time filters cannot participate directly in traversal semantics. Temporal querying is first-class. Time constraints participate directly in graph traversal. Pricing Costs increase with sharding, coordination overhead, Atlas dependency, and duplicated subsystems. Unified engine eliminates the need for separate search, vector, and graph systems. Costs scale linearly. 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 ## Common questions about MongoDB How is SurrealDB different from MongoDB? Can SurrealDB replace MongoDB? How does SurrealDB's query language compare to MongoDB's? GET STARTED ## Migrate from MongoDB Documents you already know, plus the graphs, vectors, and SQL MongoDB leaves to other systems. ![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) [Migration guide](https://surrealdb.com/docs/build/migrating/from-other-databases/from-mongodb) ```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. 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