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:

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To quickly try out RedisGraph, launch an instance using docker: docker run -p 6379:6379 -it --rm redislabs/redisgraph

Give it a try ¶
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> 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?> GRAPH.QUERY MotoGP "MATCH (r:Rider)-[:rides]->(t:Team) WHERE = 'Yamaha' RETURN,"
1) 1) ""
   2) ""
2) 1) 1) "Valentino Rossi"
      2) "Yamaha"
3) 1) "Query internal execution time: 0.625399 milliseconds"

How many riders represent team Ducati?> 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"

Tags: storage   graph  

Last modified 01 July 2021