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---

# FalkorDB Docs
# FalkorDB

[![Docker Hub](https://img.shields.io/docker/pulls/falkordb/falkordb?label=Docker)](https://hub.docker.com/r/falkordb/falkordb/)
[![Discord](https://img.shields.io/discord/1146782921294884966?style=flat-square)](https://discord.gg/ErBEqN9E)

FalkorDB is a graph database built on Redis. This graph database uses [GraphBLAS](http://faculty.cse.tamu.edu/davis/GraphBLAS.html) under the hood for its [sparse adjacency matrix](https://en.wikipedia.org/wiki/Adjacency_matrix) graph representation.
FalkorDB is a blazing fast graph database used for low latency & high throughput scenarios, under the hood it runs [GraphBLAS](http://faculty.cse.tamu.edu/davis/GraphBLAS.html) to perform graph operations using sparse linear algebra.

## Primary features

* Adopting the [Property Graph Model](https://github.com/opencypher/openCypher/blob/master/docs/property-graph-model.adoc)
* Nodes (vertices) and Relationships (edges) that may have attributes
* Nodes can have multiple labels
* Relationships have a relationship type
* Supports [OpenCypher](http://www.opencypher.org/) query language with proprietary extensions
* Offers Full-Text Search, Vector Similarly & Numeric indexing.
* Interacts via either [RESP](https://redis.io/docs/reference/protocol-spec/) and [Bolt](https://en.wikipedia.org/wiki/Bolt_(network_protocol)) protocols
* Graphs represented as sparse adjacency matrices
* Queries are translated into linear algebra expressions
* [OpenCypher](http://www.opencypher.org/) with proprietary extensions as a query language
* Support of both [RESP](https://redis.io/docs/reference/protocol-spec/) and [Bolt](https://en.wikipedia.org/wiki/Bolt_(network_protocol))
* Indexing - Full-Text Search, Vector Similarly & Numeric

To see FalkorDB in action, visit [Demos](https://github.com/FalkorDB/FalkorDB/tree/master/demo).

You can also pick getting started [demos for the leading programming languages](https://github.com/FalkorDB/demos), such as Java, Python & NodeJS.
## Give it a try

## Docker

To quickly try out FalkorDB, launch an instance using docker:
Launch an instance using docker, or use our [sandbox](https://cloud.falkordb.com/sandbox)

```sh
docker run -p 6379:6379 -it --rm falkordb/falkordb:latest
```

### Give it a try

After you load FalkorDB, 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 championship. Once created, we'll start querying our data.

### With `redis-cli`

```sh
$ 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) "Cached execution: 0"
6) "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?

```sh
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) "Cached execution: 0"
2) "Query internal execution time: 0.625399 milliseconds"
```

How many riders represent team Ducati?

```sh
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) "Cached execution: 0"
2) "Query internal execution time: 0.624435 milliseconds"
```

## Building
Once loaded you can interact with FalkorDB using any of the supported [client libraries](https://github.com/falkorDB/falkordb#Client-libraries)

Requirements:
Here we'll use [FalkorDB Python client](https://pypi.org/project/FalkorDB/) 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.

* Clone the FalkorDB repository: `git clone --recurse-submodules -j8 https://github.com/FalkorDB/FalkorDB.git`

* On Ubuntu Linux, run: `apt-get install build-essential cmake m4 automake peg libtool autoconf python3`

* On OS X, verify that `homebrew` is installed and run: `brew install cmake m4 automake peg libtool autoconf`.
* The version of Clang that ships with the OS X toolchain does not support OpenMP, which is a requirement for FalkorDB. One way to resolve this is to run `brew install gcc g++` and follow the on-screen instructions to update the symbolic links. Note that this is a system-wide change - setting the environment variables for `CC` and `CXX` will work if that is not an option.

To build, run `make` in the project's directory.

Congratulations! You can find the compiled binary at: `src/falkordb.so`

## Using FalkorDB

Before using FalkorDB, you should familiarize yourself with its commands and syntax as detailed in the
[command reference](/commands).

You can call FalkorDB's commands from any Redis client.

### With `redis-cli`
```python
from falkordb import FalkorDB

```sh
$ redis-cli
127.0.0.1:6379> GRAPH.QUERY social "CREATE (:person {name: 'roi', age: 33, gender: 'male', status: 'married'})"
```
# Connect to FalkorDB
db = FalkorDB(host='localhost', port=6379)

### With any other client
# Create the 'MotoGP' graph
g = db.select_graph('MotoGP')
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'})""")

You can interact with FalkorDB using your client's ability to send raw Redis commands.
The exact method for doing that depends on your client of choice.
# Query which riders represents Yamaha?
res = g.query("""MATCH (r:Rider)-[:rides]->(t:Team)
WHERE t.name = 'Yamaha'
RETURN r.name""")

#### Python example
for row in res.result_set:
print(row[0])

This code snippet shows how to use FalkorDB with raw Redis commands from Python using
[redis-py](https://github.com/redis/redis-py):
# Prints: "Valentino Rossi"

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

r = redis.Redis()
reply = r.graph("social").query("MATCH (r:Rider)-[:rides]->(t:Team {name:'Ducati'}) RETURN count(r)")
```
print(row[0])
# Prints:
```
For additional demos please see visit [Demos](https://github.com/FalkorDB/demos).

## Client libraries

Language-specific clients have been written by the community and the FalkorDB team for 6 languages.

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

## Data import

The falkordb team maintains the [falkordb-bulk-loader](https://github.com/falkordb/falkordb-bulk-loader) for importing new graphs from CSV files.

The data format used by this tool is described in the [GRAPH.BULK implementation details](/design/bulk_spec).
When loading large graphs from CSV files, we recommend using [falkordb-bulk-loader](https://github.com/falkordb/falkordb-bulk-loader)

## Mailing List / Forum

Got questions? Feel free to ask at the [FalkorDB forum](https://github.com/FalkorDB/FalkorDB/discussions).
Got questions? Please contact us at the [FalkorDB forum](https://github.com/FalkorDB/FalkorDB/discussions).

## License

FalkorDB is licensed under the [the Server Side Public License v1 (SSPLv1)](https://github.com/FalkorDB/FalkorDB/blob/master/LICENSE.txt).
FalkorDB is licensed under the [the Server Side Public License v1 (SSPLv1)](https://github.com/FalkorDB/FalkorDB/blob/master/LICENSE.txt).

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