Visit on the Neo4j download website https://neo4j.com/download/

When you click on the Download button, you will get a screen to register yourself to receive the activation key for Neo4j Desktop as below:

When you click on the download button, a new screen will appear that will contain the key as shown below and the downloading will start.

Copy and keep the Activation Key at a safe location that we will use for software registration step.

Go the directory where installation file .AppImage is downloaded, and execute the following command

chmod +x neo4j-desktop-1.5.9-x86_64.AppImage

./neo4j-desktop-1.5.9-x86_64.AppImage  

If you get the error like below:

dlopen(): error loading libfuse.so.2

AppImages require FUSE to run. 
You might still be able to extract the contents of this AppImage 
if you run it with the --appimage-extract option. 
See https://github.com/AppImage/AppImageKit/wiki/FUSE 
for more information

Then run the following commands:

sudo add-apt-repository universe
sudo apt install libfuse2

After that you can execute again the command

./neo4j-desktop-1.5.9-x86_64.AppImage

And you will see the output similar to following:

[14:50:00.780] [info]  ● ● ● Starting Neo4j Desktop 1.5.9 @ Linux 6.2.0-35-generic, Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz}
libva error: vaGetDriverNameByIndex() failed with unknown libva error, driver_name = (null)
[Nest] 636834  - 11/07/2023, 2:50:01 PM     LOG [NestFactory] Starting Nest application...
[Nest] 636834  - 11/07/2023, 2:50:01 PM     LOG [InstanceLoader] DeprecatedGraphQLModule dependencies initialized +75ms
[Nest] 636834  - 11/07/2023, 2:50:01 PM     LOG [InstanceLoader] GraphQLSchemaBuilderModule dependencies initialized +0ms
[Nest] 636834  - 11/07/2023, 2:50:01 PM     LOG [InstanceLoader] GraphQLModule dependencies initialized +1ms
[14:50:01.247] [info]  Initializing persistence
[Nest] 636834  - 11/07/2023, 2:50:01 PM     LOG [GraphQLModule] Mapped {/graphql, POST} route +87ms
[Nest] 636834  - 11/07/2023, 2:50:01 PM     LOG [NestApplication] Nest application successfully started +1ms
[14:50:01.333] [info]  ● ● ● GraphQL server is running @ http://127.0.0.1:11001
[14:50:01.341] [info]  Creating persistent store - projects
[14:50:01.360] [info]  Creating persistent store - databases
[14:50:01.363] [info]  Creating persistent store - userData
[14:50:01.369] [info]  Creating persistent store - graphApps
[14:50:01.372] [info]  Creating persistent store - plugins
[14:50:01.376] [info]  Creating persistent store - distributions

And a window Neo4j Desktop with license agreement will appear as follows:

Next is the Software registration page. Here you need to enter the activation key that you received at the time of software download.

After successful registration, you will see the installation screen as below:

After the successful installation you will see a message as below. Click Ok

And, finally you have Neo4j Desktop screen 😊

To open the example project Movie DBMS click on the Open button as shown in the picture below:

Et Voilà! You have a working Neo4j graph database up and working with an example database.

2. Using Cypher Queries on Example Graph Database

Click on the left-side top vertical menu icon to see the database information such as Node labels and Relationship types. You can also see the Property Keys and other DBMS information as shown in the image below.

Let’s execute a few Cypher commands to play with Neo4j graph database. We can the graph schema visualization of this example movie database Call db.schema.visualization , we will get following output

1. Let’s count the number of nodes in movie database. Execute the following query

MATCH ()
RETURN count(*) as count

And we get the output count 169

2. Count all the nodes with label Person and Movie

MATCH (:Person)
RETURN count(*) as count

MATCH (:Movie)
RETURN count(*) as count

3. Count all the relationships:

MATCH ()-[r]->()
RETURN count(r) as count

4. Find the count of number of relationship where the relationship type is ACTED_IN

MATCH ()-[r:ACTED_IN]->()
RETURN count(r) as count

5. Count relationships of multiple types. Like count the total number of relationship where relationship type name is ACTED_IN OR DIRECTED

MATCH ()-[r:ACTED_IN|DIRECTED]->()
RETURN count(r) as count

5. Let’s count the relationship type with node labels. For example, count all the nodes with label Person with relationship type ACTED_IN

MATCH (:Person)-[r:ACTED_IN]->()
RETURN count(r) as count

6. Count the number of relationships where relationship type is ACTED_IN and node label is Person and Movie . So the we will say what are persons who acted_in movie.

MATCH (:Person)-[r:ACTED_IN]->(:Movie)
RETURN count(r) as count