FalkorDB

Docker Hub Discord

Try Free

FalkorDB is a blazing fast graph database used for low latency & high throughput scenarios, under the hood it runs GraphBLAS to perform graph operations using sparse linear algebra.

Primary features

Give it a try

Launch an instance using docker, or use FalkorDB Clouds

docker run -p 6379:6379 -p 3000:3000 -it --rm falkordb/falkordb:latest

Once loaded you can interact with FalkorDB using any of the supported client libraries

Here we’ll use FalkorDB Python client to 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.

from falkordb import FalkorDB

# Connect to FalkorDB
db = FalkorDB(host='localhost', port=6379)

# Create the 'MotoGP' graph
g = db.select_graph('MotoGP')
# Clear out this graph in case you've run this script before.
g.delete()
g.query("""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'})""")

# Query which riders represents Yamaha?
res = g.query("""MATCH (r:Rider)-[:rides]->(t:Team)
                 WHERE t.name = 'Yamaha'
                 RETURN r.name""")

for row in res.result_set:
    print(row[0]) # Prints: "Valentino Rossi"

# Query how many riders represent team Ducati ?
res = g.query("""MATCH (r:Rider)-[:rides]->(t:Team {name:'Ducati'}) RETURN count(r)""")

print(res.result_set[0][0]) # Prints: 1

For additional demos please see visit Demos.

Client libraries

Language-specific clients have been written by the community and the FalkorDB team. The full list and links can be found on the Clients page.

Data import

When loading large graphs from CSV files, we recommend using falkordb-bulk-loader

Mailing List / Forum

Got questions? Please contact us at the FalkorDB forum.

License

FalkorDB is licensed under the the Server Side Public License v1 (SSPLv1).