5 database paradigms and their use cases.

Code on laptop

The database paradigms I will be covering in this blog are

  1. Relational
  2. Key-Value
  3. Wide-Column
  4. Document
  5. Graph

What are database paradigms?

storing data for applications and businesses is stored in databases. These are 6 of the most popular database types and their use cases.

  1. Relational Databases Data is the modern world is highly relational and connected. Relational databases make that easier with connecting models. It typically contains rows and columns similar in a SQL formats but it will contain relations by storing primary keys as values. It is easily queried although with the data being highly relational write time is longer. Popular database examples of this type are PostgreSQL(my personal favorite), MySQL, Microsoft SQL Server, Oracle Database. This type of database is useful for general use and things like accounts, users, transactions, and the general data storage.

  2. Key-Value Databases Key-Value databases excel in things such as speed. They store data quite like the name, in a giant key-value storage. The most popular key-value database, redis, is typically used for things like session storage. Its quite read and write time allows for it to have faster response time but since key-value databases are often meant for less secure data. Data that would have little impact when something goes wrong because Redis is stored in memory instead of hard drive. This is for faster performance. Popular examples of this database are Amazon DynamoDB, Redis, Oracle NoSQL DB. This type of database is most often used in parallel with relational databases. The key-value database will store things like sessions, cookies, jwt tokens, logging while the relational database will store the important things such as accounts, transactions, products.

  3. Wide-Column Wide column databases takes key values and provides column connected values. This means the key will often have many values associated with it. This makes it easier and somewhat relational. Wide-Column is also schema-less and does not support JOINS. The query language for this database, cql(similar to sql), provides a standardized way to query data. Popular databases for this are HBASE and Cassandra. Wide-Column is best suited for high-write low-read operations and provides a decentralized way of data storage. This makes it easy to scale horizontally or vertically.

  4. Document Document databases are another popular way of storing general purpose data. It is often structured as a giant JSON object. It is first in documents, then in collections, and then indexes. Document does not support JOINS and is schema-less allowing freedom. It does not have a query language is can only be somewhat relational in its data. The trade off for document databases is that it allows fast read time and high write time as updating data as the data is more complex. Popular database examples in this type are MongoDB, DocumentDB, Firebase. Document databases fail when data is highly relational such as users that have friends, that have followers, that have posts, that have likes etc.

  5. Graph Graph databases is organized as nodes and relationships between them with edges. The most popular Graph Database is DGraph. Unlike relational databases accounts would be directly linked to likes on a post rather than the middleman relation of the post. This allows for faster queries but a slower write time.


My personal favorite database is still PostgreSQL which is still the most popular to this day although with new technologies emerging we are bound to see better options that will reinvent the way we store data.