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Databases Intermediate

What is Graph Database?

A database that uses graph structures with nodes, edges, and properties to store and query highly connected data.

Graph databases excel at storing and traversing relationships between entities. Unlike relational databases where joins become expensive with depth, graph databases traverse connections in constant time per hop. Neo4j is the most popular graph database, using the Cypher query language. Use cases include social networks, recommendation engines, fraud detection, knowledge graphs, and network topology. PostgreSQL also supports graph-like queries through recursive CTEs and the Apache AGE extension. Graph databases shine when the relationships between data are as important as the data itself.

Related Terms

Connection Pool
A cache of database connections that can be reused, avoiding the overhead of creating new connections for each request.
Soft Delete
A pattern where records are marked as deleted with a flag or timestamp rather than being physically removed from the database.
Migration
A version-controlled change to a database schema that can be applied and reversed systematically.
Database Index Types
Different index structures (B-tree, Hash, GIN, GiST, BRIN) optimized for various query patterns and data types.
Connection String
A formatted string containing all parameters needed to establish a connection to a database server.
Trigger
A database object that automatically executes a specified function when certain events (INSERT, UPDATE, DELETE) occur on a table.
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