--- title: "20: Creating graph edges | SurrealDB University" description: "Creating graph edges. A step in the guided Tour of SurrealDB, with examples you can run as you read." url: https://surrealdb.com/learn/tour/page-20 --- ![Course content preview](https://surrealdb.com/assets/static/town.D95IYf2V.avif) Course chapters [Back to courses](https://surrealdb.com/learn) [Welcome to the Tour of SurrealDB!](https://surrealdb.com/learn/tour) [1: Connecting to a database](https://surrealdb.com/learn/tour/page-01) [2: Creating records](https://surrealdb.com/learn/tour/page-02) [3: Using the ONLY keyword](https://surrealdb.com/learn/tour/page-03) [4: Non-ASCII record IDs](https://surrealdb.com/learn/tour/page-04) [5: Parentheses, indexing, and fields](https://surrealdb.com/learn/tour/page-05) [6: Deleting records](https://surrealdb.com/learn/tour/page-06) [7: Field order in objects](https://surrealdb.com/learn/tour/page-07) [8: Tips when selecting records](https://surrealdb.com/learn/tour/page-08) [9: Casting and aliases](https://surrealdb.com/learn/tour/page-09) [10: Affixes](https://surrealdb.com/learn/tour/page-10) [11: Updating records](https://surrealdb.com/learn/tour/page-11) [12: Linking records](https://surrealdb.com/learn/tour/page-12) [13: Viewing the database as a whole](https://surrealdb.com/learn/tour/page-13) [14: Schemafull and schemaless](https://surrealdb.com/learn/tour/page-14) [15: Viewing the schema](https://surrealdb.com/learn/tour/page-15) [16: Literal types and assertions](https://surrealdb.com/learn/tour/page-16) [17: INSERT and using JSON](https://surrealdb.com/learn/tour/page-17) [18: FOR loops](https://surrealdb.com/learn/tour/page-18) [19: Basic graph relations](https://surrealdb.com/learn/tour/page-19) [20: Creating graph edges](https://surrealdb.com/learn/tour/page-20) [21: Querying graph relations](https://surrealdb.com/learn/tour/page-21) [22: Graph relations at greater depth](https://surrealdb.com/learn/tour/page-22) [23: Adding and improving data](https://surrealdb.com/learn/tour/page-23) [24: Defining events](https://surrealdb.com/learn/tour/page-24) [25: Defining indexes](https://surrealdb.com/learn/tour/page-25) [26: Improving the schema](https://surrealdb.com/learn/tour/page-26) [27: Visualising graph paths](https://surrealdb.com/learn/tour/page-27) [28: Recursive queries: setup](https://surrealdb.com/learn/tour/page-28) [29: Recursive queries](https://surrealdb.com/learn/tour/page-29) [30: More on recursive queries](https://surrealdb.com/learn/tour/page-30) [31: AI vector search](https://surrealdb.com/learn/tour/page-31) [Done the tour!](https://surrealdb.com/learn/tour/page-32) # 20: Creating graph edges To create a graph relation, we can use the [`RELATE`](https://surrealdb.com/docs/reference/query-language/statements/relate) statement. The syntax for this statement is `RELATE record->graph_table_name->record`, leading to quite readable syntax since graph tables are usually a verb or similar word ("place employs person", "person likes book", and so on). Here is what some typical `RELATE` statements look like. ``` -- Create writer->wrote->blog pathRELATE writer:one->wrote->blog:one;-- Create reader->likes->magazine pathRELATE reader:one->likes->magazine:one SET stars_out_of_ten = 7.5; -- and give it a field too if we want ``` ![Surrealist Icon](https://surrealdb.com/assets/static/fdfe2c20f5941d5e.D0guSOhZ.webp) Run Query Output · Query 1 ```surql [ { id: wrote:7l04nq3umzufbemaldlz, in: writer:one, out: blog:one } ] ``` Output · Query 2 ```surql [ { id: likes:jd17lotl4nnyf06jl2ng, in: reader:one, out: magazine:one, stars_out_of_ten: 7.5f } ] ``` Using this syntax, we can now create the employees inside a `FOR` loop and link them to the library at the same time. Inside the query below is an array of objects that contain the employee data. Inside each loop, we can create a single `person` record using the `ONLY` keyword and assign the output to a parameter called `$created`. This parameter can then be used in the statement `RELATE $created->works_at->place:surreal_library`. ``` FOR $person IN [ { age: 30, name: 'Sara Bellum' }, { age: 25, name: 'Lydia Wyndham' }, { age: 45, name: 'Samm Schwartz' }] { LET $created = CREATE ONLY person SET age = $person.age, name = $person.name; RELATE $created->works_at->place:surreal_library;}; ``` ![Surrealist Icon](https://surrealdb.com/assets/static/fdfe2c20f5941d5e.D0guSOhZ.webp) Run Query Now that the relations have been created, we can look at the `works_at` table to see what is inside. Querying in this way is no different from any other table. ``` SELECT * FROM works_at; ``` ![Surrealist Icon](https://surrealdb.com/assets/static/fdfe2c20f5941d5e.D0guSOhZ.webp) Run Query Each `works_at` record has its own random ID, has a `person` at the `in` field (the initiator of the relation), and a `place` at the `out` field (the target of the relation). Output ```surql [ { id: works_at:3o8n3jmqx1uok41rjxq7, in: person:g94fc1nqsraaatplddyh, out: place:surreal_library }, { id: works_at:f3ghd88elmvs1jwfhpoc, in: person:qpk3htqruhvd469pox0r, out: place:surreal_library }, { id: works_at:j2yf2jdnmponak0v3q0q, in: person:6kittp2n5lwpjzgu29jt, out: place:surreal_library } ] ``` You can always query graph edges in this way if you want. For example, this query shows all the details for all the people at the `in` part of `works_at`, which in this case shows our `person` records. ``` SELECT in.* FROM works_at; ``` ![Surrealist Icon](https://surrealdb.com/assets/static/fdfe2c20f5941d5e.D0guSOhZ.webp) Run Query Output ```surql [ { in: { age: 45, id: person:f0z8cabmok8m9xn00lfu, name: 'Samm Schwartz' } }, { in: { age: 30, id: person:zfdzeawmuqh2mm498edj, name: 'Sara Bellum' } }, { in: { age: 25, id: person:ocp2l14l4nbgo60mnhgt, name: 'Lydia Wyndham' } } ] ``` However, the `->` and `<-` arrows used to create relations are also used to quickly move from one path to the next, and it is this syntax that is usually used when querying them. We'll give this syntax a try on the next page. At a glance **You are on** Chapter 20 of 32 **Chapters** 32 **Format** Text, with queries you can run **Runs in** SurrealDB Studio, in the browser **Cost** Free **Then take** [SurrealDB Fundamentals](https://surrealdb.com/learn/fundamentals) [Next: 21: Querying graph relations](https://surrealdb.com/learn/tour/page-21) ## Continue ### [19: Basic graph relations](https://surrealdb.com/learn/tour/page-19) Previous ### [21: Querying graph relations](https://surrealdb.com/learn/tour/page-21) Next lesson THE PLATFORM ## Everything an application and its agents know. Five surfaces, one engine. Database Document, graph, vector, time-series and relational in one engine. ![Five data models as dotted tiles: documents, graph, vector, time-series and relational](https://surrealdb.com/assets/static/platform-database.DUdumYDz.avif) Read more [Database](https://surrealdb.com/surrealdb) Agent Memory What an agent learns, with its source and its time, in the same engine. ![A timeline of remembered facts, each with its source](https://surrealdb.com/assets/static/platform-agent-memory.Cvv8D5Wl.avif) Read more [Agent Memory](https://surrealdb.com/agent-memory) Cloud Managed clusters in the regions you choose, scaled on demand. ![Clusters in three regions on a world map, each running or scaling](https://surrealdb.com/assets/static/platform-cloud.--QZnaVi.avif) Read more [Cloud](https://surrealdb.com/cloud) Studio Query, explore and design the schema from the browser. ![A SurrealQL query in Studio and the schema graph under it](https://surrealdb.com/assets/static/platform-studio.7ykBFNLq.avif) Read more [Studio](https://surrealdb.com/studio) MCP Every model that speaks MCP reaches the database and the memory directly. ![Three models connected through MCP to the database and Agent Memory](https://surrealdb.com/assets/static/platform-mcp.D_oH0_wm.avif) Read more [MCP](https://surrealdb.com/mcp) IN PRODUCTION ## Trusted at scale. Samsung, Nvidia, Verizon, Tencent, and Walmart run on SurrealDB. 14,000+ Developers building on SurrealDB Cloud 4M+ Developers building on SurrealDB worldwide FROM THE TEAMS > SurrealDB gives us a foundation where we can unify semantic search, knowledge graphs, and AI-driven decision making without stitching together multiple systems. 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