Exploring Key-Value, Document, Column, and Graph Database Models
This article explains four fundamental database data models—key‑value pair, document, column, and graph—detailing their structures, scalability characteristics, and typical implementations such as Redis, MongoDB, HBase, and Neo4j.
KVP (Key-Value Pair) Model
A simple, highly flexible and extensible model consisting of two associated data items. As data volume grows, computation increases, making databases using KVP models scale exponentially.
Typical examples: Redis, Riak.
Document Model
There are two types of document databases: (1) full‑document stores, like repositories for Word documents or complete web pages; (2) component‑document stores, holding parts of documents. They store data in JSON or BSON, making storage and retrieval very convenient.
Typical examples: MongoDB, CouchDB.
Column Model
Data is stored in columnar structures rather than rows, which is ideal for large, diverse datasets; adding new columns is straightforward.
Typical examples: HBase.
Graph Model
Uses graph structures to store and query data, placing structured data in a network of nodes and edges instead of tables, suitable for scenarios with many interrelated data points.
Typical examples: Neo4j.
Signed-in readers can open the original source through BestHub's protected redirect.
This article has been distilled and summarized from source material, then republished for learning and reference. If you believe it infringes your rights, please contactand we will review it promptly.
Java High-Performance Architecture
Sharing Java development articles and resources, including SSM architecture and the Spring ecosystem (Spring Boot, Spring Cloud, MyBatis, Dubbo, Docker), Zookeeper, Redis, architecture design, microservices, message queues, Git, etc.
How this landed with the community
Was this worth your time?
0 Comments
Thoughtful readers leave field notes, pushback, and hard-won operational detail here.