Introduction to graph databases Roksolana Diachuk, WWCode Kyiv Lead, Data Engineer at Ciklum

Relational vs. non-relational ● Relational DBs store data in tables and rows. NoSQL DBs store data in various formats - documents, graphs ● Relational DBs use unified query language - SQL. NoSQL DBs may have various query languages. ● Relational DBs provide ACID guarantees that is why they are more reliable. NoSQL DBs usually do not have strict guarantees (they may provide BASE guarantees) ● It is easier to scale NoSQL DBs and change the schema. While in relational DBs the schema is fixed. @dead_flowes22

Definition Graph database is NoSQL database which is based on the graph theory. All the data is expressed with the help of nodes (entities) and edges (relationships between entities). @dead_flowes22

Why would you care about graph databases ● Flexibility (for volume increase) ● High performance ● Agility (for schema) @dead_flowes22

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Neo4j query @dead_flowes22

Neo4j Neo4j is one of the most popular graph databases. The query language is Cypher which is similar to SQL. Neo4j management: 1. Cypher shell 2. Admin 3. REST API @dead_flowes22

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Neo4j queries visualization @dead_flowes22

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Real-time recommendation systems @dead_flowes22

Fraud detection @dead_flowes22

Master data management @dead_flowes22

Graphs aided search @dead_flowes22

Compliance and privacy solutions @dead_flowes22

Prototype creation stages ● Dataset research ● Database design (edges and relationships) ● Dataset import ● Queries on dataset @dead_flowes22

Conclusion Building a prototype with graph databases will help you to discover how graph databases can be integrated into your system and whether your data can be queried and managed more efficiently. @dead_flowes22

Thank you for attention!