{"id":6103,"date":"2018-12-07T18:32:40","date_gmt":"2018-12-07T18:32:40","guid":{"rendered":"https:\/\/cheesecakelabs.com\/blog\/?p=6103\/"},"modified":"2022-08-31T13:46:23","modified_gmt":"2022-08-31T13:46:23","slug":"starting-graph-databases-quick-look-neo4j","status":"publish","type":"post","link":"https:\/\/cheesecakelabs.com\/blog\/starting-graph-databases-quick-look-neo4j\/","title":{"rendered":"Starting with Graph Databases: A Quick look into Neo4j"},"content":{"rendered":"\n

Let\u2019s talk about Neo4j, a graph database that recently has attracted a significant number of fans.<\/span><\/p>\n\n\n\n

My goal is for you to have a brief (I promise to be quick) vision of how it works and to give you some examples to make it more tangible.<\/span><\/p>\n\n\n\n\n\n\n\n

We are used to write data using tables, to relate them through primary keys and, by looking directly at the data, you only see IDs.<\/span><\/p>\n\n\n\n

Graph databases were designed mainly so that this doesn’t happen.<\/span><\/p>\n\n\n\n

Its purpose is for you to have a complete understanding when looking at the data.<\/span><\/p>\n\n\n

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Example of a simple school database diagram.<\/figcaption><\/figure>\n<\/div>\n\n\n

First of all, to understand the advantage of graph databases, it’s very good to know a few concepts that reinforce the idea of software close to the business rules.<\/span><\/p>\n\n\n\n

For that, it is worth reading <\/span>Domain-Driven Design<\/span><\/a>, where the model should be as close as possible to the business. <\/span><\/p>\n\n\n\n

In Neo4j, that is done with Cypher: a declarative SQL-inspired language for describing patterns in visual graphs using an ASCII syntax.<\/span><\/p>\n\n\n\n

It allows us to state what we want to select, insert, update or delete from our graph data without requiring us to describe exactly how to do it.<\/span><\/p>\n\n\n\n

To be more practical, mind the example below, where the same “query” is implemented with SQL and Cypher.<\/span><\/p>\n\n\n

 \nSELECT f.* FROM students s\nINNER JOIN person p\nON p.id = s.person_id\nINNER JOIN friend f\nON f.friend_from_id = p.id\nWHERE s.id = 45\nORDER BY p.name\n<\/code>\n<\/pre>\n\n
 \nMATCH\n(student :Student)-[FRIEND]->(person :Person)\nWHERE student.id = 45\nRETURN person\nORDER BY person.name\n<\/code>\n<\/pre>\n\n\n
Above there’s a “query” to search for a specific student’s friends, where in the traditional mode (SQL) we need to better understand the database structure and know how they relate, causing a greater use of “JOINS”. In Cypher relations are more intuitive for reading.<\/span><\/p>\n\n\n\n
Graph databases are a more natural way of storing the data.<\/span><\/p>\n\n\n\n
You don’t have to worry about tables and foreign keys and it keeps everything within two simple concepts: nodes and relations.<\/span><\/p>\n\n\n\n
Each node or relation can have its attributes and labels of identification, a way to categorize the data.<\/span><\/p>\n\n\n\n
To make it easier to understand, let\u2019s map a school in a simple way, where we have students, teachers and courses.<\/span><\/p>\n\n\n\n
How would a diagram represent this? Would you do it in a graph database? It is actually simpler than you think! Just draw it:<\/span><\/p>\n\n\n
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Now, hands-on!<\/span><\/p>\n\n\n\n
You can <\/span>install Neo4j on your computer<\/span><\/a> or do it using Docker:<\/span><\/p>\n\n\n
 \nimage: neo4j:3.4.5\nports:\n  - \"7474:7474\"\n  - \"7473:7473\"\n  - \"7687:7687\"\n<\/code>\n<\/pre>\n\n\n
Don’t forget to follow the rules and nomenclature recommendations<\/a>.<\/span><\/p>\n\n\n\n
Creating our first nodes:<\/span><\/p>\n\n\n
 \nCREATE (s)-[k:KNOWS]->(t), (t)-[ts:TEACHES]->(c), (s)-[e:ENROLLED]->(c)\nCREATE (user1:Person:Student { name: \"Natam\" })\nCREATE (user2:Person:Teacher { name: \"Natalia\" })\nCREATE (course:Course { title: \u201cMath\u201d })<\/code><\/pre>\n\n\n
Now let\u2019s relate them:<\/span><\/em><\/p>\n\n\n
\nMATCH (s:Student {name:\"Natam\"}), (t:Teacher {name:\"Natalia\"}), (c:Course {title:\"Math\"})<\/code><\/pre>\n\n\n
Now that we have our data, we need to consult it. Let\u2019s do this?<\/span><\/p>\n\n\n
\nMATCH (n) RETURN n<\/code><\/pre>\n\n\n
This command will return an overview of your graph.<\/span><\/p>\n\n\n\n
You can apply more filters and conditions to your “query”. Check this out: Neo4j Cypher Manual<\/a><\/span><\/p>\n\n\n\n
Conclusion, but already?<\/b><\/h2>\n\n\n\n
Yes! The purpose of this post is for you to get to know this incredible technology and how basic is its structure.<\/span><\/p>\n\n\n\n
If you found it interesting and want to learn more about it, try modeling applications you already know using Neo4j.<\/span><\/p>\n\n\n\n
I\u2019m sure you\u2019ll be even more surprised!<\/span><\/p>\n\n\n\n
I will leave a few links in case you want to know more concepts related to this technology.<\/span><\/p>\n\n\n\n
REFERENCES<\/h3>\n\n\n\n