RedisGraph is the first queryable Property Graph database to use sparse matrices to represent the adjacency matrix in graphs and linear algebra to query the graph.
Primary features:
To quickly try out RedisGraph, launch an instance using docker: docker run -p 6379:6379 -it --rm redislabs/redisgraph
After you load RedisGraph, you can interact with it using redis-cli.
Here we'll quickly create a small graph representing a subset of motorcycle riders and teams taking part in the MotoGP league. Once created, we'll start querying our data.
With redis-cli
$ redis-cli
127.0.0.1:6379> GRAPH.QUERY MotoGP "CREATE (:Rider {name:'Valentino Rossi'})-[:rides]->(:Team {name:'Yamaha'}), (:Rider {name:'Dani Pedrosa'})-[:rides]->(:Team {name:'Honda'}), (:Rider {name:'Andrea Dovizioso'})-[:rides]->(:Team {name:'Ducati'})"
1) 1) Labels added: 2
2) Nodes created: 6
3) Properties set: 6
4) Relationships created: 3
5) "Query internal execution time: 0.399000 milliseconds"
Now that our MotoGP graph is created, we can start asking questions. For example: Who's riding for team Yamaha?
127.0.0.1:6379> GRAPH.QUERY MotoGP "MATCH (r:Rider)-[:rides]->(t:Team) WHERE t.name = 'Yamaha' RETURN r.name, t.name"
1) 1) "r.name"
2) "t.name"
2) 1) 1) "Valentino Rossi"
2) "Yamaha"
3) 1) "Query internal execution time: 0.625399 milliseconds"
How many riders represent team Ducati?
127.0.0.1:6379> GRAPH.QUERY MotoGP "MATCH (r:Rider)-[:rides]->(t:Team {name:'Ducati'}) RETURN count(r)"
1) 1) "count(r)"
2) 1) 1) (integer) 1
3) 1) "Query internal execution time: 0.624435 milliseconds"
Last modified 20 January 2023