If there’s one thing that drives businesses, it’s data. Data has led the way in business decisions such as marketing, financing, hiring, and so many other areas. In fact, without data, most businesses would be utterly and profoundly lost.
Data – you want it, you need it.
But how do you store it? Most businesses answer that question with a single response—databases. From small businesses to enterprise-level companies, databases are crucial to collecting, storing, and using that information.
But did you know there are two different types of databases? Well, there are, and each of these databases are better suited for specific tasks and/or business sizes. One of these databases can be used by just about anyone, whereas the other requires much more technical skill (such as the one essential for .NET developers).
Let’s take a look at the two primary types of databases and discover which might be best suited for your business.
Relational Databases
This type of database is the most common you’ll find. A relational database is a collection of tables, each of which uses a schema (made up of rows and columns) to represent various fixed attributes and data types for the items contained within.
Each relational database includes the means for reading, creating, updating, and deleting data. Generally speaking, the means by which you interact with the data in relational databases if through Structured Query Language (SQL) statements. However, there are GUI applications for this purpose, such as phpMyAdmin.
The primary characteristic of relational databases is data integrity, and the most widely used databases of this type are:
- MySQL – An open-source relational database that runs on nearly all platforms.
- MS SQL – The Microsoft SQL database which is available for both Windows, macOS, and Linux.
- Oracle Database – A multi-model database management system, created by Oracle Corporation.
- PostgreSQL – Another open-source database engine that focuses on standards compliance.
- DB2 – IBM’s database, designed for speed.
The primary advantages of relational databases are:
- Data integrity
- Well documented and widely distributed
- Can run on off-the-shelf hardware
- Ease of use
- ACID-compliant
The disadvantages of relational databases are:
- They do not work well with unstructured data.
- Tables do not map one-to-one with objects.
- Data migration can be complicated, due to schema construction.
The best uses for relational databases are for when you have structured data that needs to be manipulated. For example, you have a database of employees that needs to be structured such that each column entry (one column per employee) contains First Name, Last Name, Employee Number, Department, Hire Date, Age, Birthday, Address, Phone Number, and Emergency Contact. Or you have a database of products that needs to be structured such that each column entry (one per product) contains Product Name, Product SKU, Product Wholesale Price, Consumer Price, Number in Stock. These types of databases are great for powering websites like WordPress, Drupal, Joomla, OrangeCRM, and more. In fact, any website that serves up dynamic data is most likely using a relational database.
Non-Relational Database
Non-relational database (AKA NoSQL databases) rose to popularity with the proliferation of ever more complicated web-based applications. Unlike relational databases, non-relational databases do not adhere to a strict schema that dictates where data is inserted into a database. Non-relational databases allow for both unstructured and semi-structured data.
To simplify this, non-relational databases do not use tables filled with rows and columns. Instead, they make use of the storage model optimized for the data being stored. Because of this, there are different types of non-relational databases.
The types of non-relational database stores are:
- Key-Value Stores (such as Redis and Amazon DynamoDB) – stores only key-value pairs to provide very basic functionality. Each key will have an associated value.
- Wide Column Stores (such as Casandra and HBase)- store data in single row records. These are similar to key-value stores, only with multiple values associated with a key.
- Document Stores (such as MongoDB and Couchbase) – store data in JSON-formatted documents, where the document name is the key and the contents of the document are the associated value.
- Graph Databases (such as GraphDB Lite and OrientDB) – store data as a network of related objects, such that they can be easily represented via data visualizations and graphs.
- Search Engines (such as Elasticsearch and Splunk) – store data in JSON documents. Unlike Document Stores, these databases focus on making data easily accessible via text-based search engines.
The advantages of the non-relational database are:
- Scalability
- Flexibility
- Data can be distributed across multiple nodes
- Can store and process massive amounts of data (of any type)
Disadvantages of non-relational databases are:
- Not as mature as relational databases.
- Less available support.
- Simple queries require some programming knowledge.
- Most common business intelligence tools do not offer connectivity.
- Steeper learning curve that could require you to seek out a third party (such as .net development companies).
Which is Right For You
The answer to this question is actually relatively simple. If you need a database to store structured data, such that it can be used by common applications and services, you’ll want a relational database.
If, on the other hand, you need to store massive amounts of unstructured data, and are not looking to integrate this data into common tools, then a non-relational database is what you want.
Or, if you want to think of it in more business-centric terms:
- If you want to scale vertically, use a relational database.
- If you want to scale horizontally, use a non-relational database.
