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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

ETL (Extract, Transform, Load)
A data pipeline process that extracts data from sources, transforms it into a suitable format, and loads it into a destination system.
Connection Pool
A cache of database connections that can be reused, avoiding the overhead of creating new connections for each request.
Query Optimization
The process of improving database query performance through indexing, query rewriting, and schema design techniques.
Partitioning
A technique of dividing large database tables into smaller, more manageable segments while maintaining a single logical table.
Schema
The structure definition of a database including tables, columns, data types, relationships, indexes, and constraints.
Database Proxy
A middleware server that sits between applications and databases, providing connection pooling, load balancing, and query routing.
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