What Are the Different Types of Databases? (5 DBMS & Uses)

This article will answer the pressing question, what are the different types of databases and their uses. Firstly, it's important to note that when we talk about databases, we are not always talking about management systems. Indeed, defining a database and a DBMS (database management system) is one thing we will achieve here. 

First, we will give a quick rundown of a large list of database types and their schemas. Then, we will explore the 5 types of DBMS and check out some of their subsets.

Let's get started!

How many types of databases are there?

When it comes to categories of databases, no one official number is set in stone. You can find resources that list as few as 4 or 5 and as many as 20 types of databases. For our purposes here, we have decided to list the 13 most common types of database systems.  

What are the different types of databases and their uses?

So, you need to store many types of data and a large amount of data, right? That's why you're here. In this section, let us break down the many types of databases into top-level categories of DB types. This will help us get a clearer answer to the question, what are the different databases when we think of them grouped into larger sets of DB management systems. 

Whenever you are in the market for the best database management system, it is a good idea to know the difference between upper and lower levels of database uses. More importantly, if you're unsure what is database management, we advise you to get acquainted with the basics before moving on.

Ultimately, you do not need to have an encyclopedic memory of all the database software types, subtypes, and systems out there. In the next section, we will group them into larger categories and attempt to make sense of each in the simplest way. 
 

Main database structure types

• Relational databases
  • Oracle Database
  • MySQL
  • Microsoft SQL Server
  • PostgreSQL

• Hierarchical databases
  • IBM Information Management System
  • RDM 

• Network databases
  • Integrated Data Store
  • IDMS
  • TurboIMAGE

• Object-oriented databases
  • Db4o
  • ObjectBox
  • InterSystems Caché

• NoSQL databases
  • Document databases
  • Key-value stores
  • Column-oriented databases
  • Graph databases
    • Labeled-property graphs
    • Resource Description Framework
       

Other types of database system categorization

What follows is a more detailed breakdown of how data is stored based on other criteria, such as centralized vs decentralized databases or commercial vs. open-source databases. 

• ER model databases
  • Conceptual
  • Physical
  • Logical

• Centralized vs Distributed/Decentralized databases
  • Centralized database
  • Distributed database
• Cloud database
  • Infrastructure as a Service
  • Platform as a Service
  • Software as a Service
• Commercial database
• End-user database
  • Casual 
  • Parametric 
  • Sophisticated 
  • Standalone 
• Open-source database
• Operational database
• Personal database

What are the 5 types of database management systems and sub types? 

Now that we have made a list of database types, it is important to understand the difference between a type and a management system. Right now, we will group our DBs into a list of database management systems that includes five entries picked from above. The most significant difference is how non-relational and relational databases use different data types. They are:

1. Relational databases

2. Hierarchical databases

3. Network databases

4. Object-oriented databases

5. NoSQL databases
    

Relational databases

Our first DB type is the relational database. As the name suggests, relational databases are helpful when your data is structured to have relational values between each entry within the database. A relational database is often displayed on a table, where rows can signify entries, columns will signify attributes, and each field is a data point. RDBMS is one of the many different types of SQL databases

Relational databases are very useful for adding, deleting data, or updating data fields which can then automatically alter their relational values to other data fields. These databases follow different types of relationships too. A relational database management system can be learned with very little training, and many web applications exist which make RDBMSs even easier to master. This is one of the most common types of databases that uses field records in some cases.

Different types of database systems that fall under RDBMS

When you do the research to look at examples of relational databases that fit into this type of management system, the most common results will come from proprietary programming languages from major firms like Oracle and Microsoft. 

Oracle Database

Made by the Oracle corporation, which also makes apps for ERP and CRM, the Oracle Database is one of the most popular relational database management tools. It utilizes a mix of transaction processing and data warehousing. You can run this on-premise or in the cloud. As should be clear, Oracle uses SQL or structured language querying to run this system.

MySQL

Unlike Oracle, MySQL is an open-source relational database management program. It also runs on SQL-type data of data organization. MySQL lets users plan their data on tables, and you can do it all from a single table or multiple tables for enhanced scalability. Supposedly, big-name websites use MySQL, like Twitter, Youtube, and Facebook.

Microsoft SQL Server

Back to proprietary database systems that do relational database management, next, we have one from the Microsoft Corporation. Microsoft SQL Server runs on what the company calls TDS, or Tabular Data Streams, which serve as an intermediary between a server and a user. It also works with columns that could be primitive or multi-layered.

PostgreSQL

PostgreSQL is an open-source relational database and therefore, it is also free to use. One of its core attributes is extensibility, which means the ability to easily scale up and expand its database for growth purposes. PostgreSQL is common among everything from data warehouses to web services and even single database storage machines. 

Hierarchical databases

Our second of the DBMS types is the hierarchical database management system. The Hierarchical DBMS has a tree structure, which means there are metadata groups at the roots, also called parent data, and from there, more data sets branch out, called child records. Hierarchical DBMS is all about parent-child relational data in this way, and to remain simple, each child is only tied to one parent record.

The pro of this hierarchical DBMS is that information retrieval is often very speedy and straightforward. However, the drawback here is when a data record is forced to be related to a single parent record, and this might oversimplify the relationship between data from multiple sources. With Hierarchical DBMS, in most cases, access to every table and field in a database is a necessity for every user.

Database management system types that fall under hierarchical DBMS

The simple yet effective tree-like structure of hierarchical database management has been around for a long time, with one of its most recognizable uses being family dynasties using the family tree. The DBMS types that fall under hierarchical structures are generally limited to one by IBM and the other by Raima.

IBM Information Management System

The International Business Machines Corporation is familiar to many people by its acronym IBM. They make a hierarchical DBMS, and these databases are often used by similarly sized enterprises. A strong element of this system is its transaction processing tools that divide information into smaller binary units, which allow you to store network data with consistency and structure. It should be noted that the IBM Information Management System can work alongside IBM's Db2, which does relational management, and this combination is great for data warehousing.

RDM 

Raima is a multinational tech company, and the maker of another common hierarchical DBMS called RDM, or Raima database manager. This is an embedded database, which means it runs very smoothly inside another application or program. It can handle local networking or wide-zone networking, as well as do on-disk or in-memory storage. Different packages include RDM Core and RDM Enterprise.
 

Network databases

The network database might so far be the most sophisticated DBMS out of all the various databases we've looked at so far. These types of databases are also called information utilities or data banks. A network database is based on more complicated networked relationships between data records than how basic relational or hierarchical databases are often used. The network structure allows for more diverse connections that are less like a tree and more like a rhizome, where, for example, one member node record can have more than one occupier node, as is how relational databases work.

The network database system is most advantageous when most of your data nodes will have many-to-many relationships among one another and to the whole group. These databases are great for highly complicated and sophisticated business data with many inputs and attributes, but for this reason, it is also vulnerable if any single data node is faulty.

Different database types that fall under Network DBMS

As one of the most useful types of database management systems, network DBMS has many protocols that fall under this heading. Below are some of the most commonly talked about schema for the data, though it should be noted that others like Raima's could be included here as well.

Integrated Data Store

This one was originally designed to handle the massive database management needs of the giant company General Electric. Because of this, it is almost an industry-standard tool for many other similarly-sized enterprises. Integrated Data Store is also the basis of the Committee on Data Systems Languages. 

IDMS

The Integrated Database Management System, or IDMS, is the evolution of the IDS, or Integrated Data Store, having come from the same labs. It uses a model set by CODASYL, or the Committee on Data Systems Languages, and lets users add or access data records according to the common business-oriented language model. IDMS uses files for data storage which are then turned into pages that can be mapped onto data areas.

TurboIMAGE

TurboIMAGE started out as the IMAGE DBMS developed by the hardware company Hewlett-Packard. This is another strong contender for network systems when a relational system won't cut it. These databases offer a front-end processor which makes it simple to run SQL queries, and this sometimes means it is called IMAGE/SQL in its current edition.
 

Object-oriented databases

Perhaps the best way to think about OODBMS is that, unlike the above DBMS types, the especially relational, object-oriented programming language does not use tables. In these cases, data nodes are considered objects which are developed or built, and from there, can be stored or replicated with modifications. Another way to think about it is that an object contains data and code within it. The code includes methods and procedures for reading and writing the data. This data management system also employs atomicity allowing for multiple data items and operations to be grouped into a single object.

The benefits of OODBMS types are that it is very efficient to access and replicate data objects in order to expand a database's scalability rapidly. This allows for a sort of data mixing and matching, which is highly applicable to databases that handle multimedia, among other things. One thing to note, however, is that OODBMS are not easy to set up, especially if structured data must be converted from relational database systems. 

Types of DBMS that fall under OODBMS

Being that OODBMS are for more complicated database business needs, it is as expected that there are many different database management programs that attempt to serve object database purposes. Most employ some or all of the following attributes: polymorphism, inheritance, encapsulation, and abstraction.

Db4o

This one is an open-source OODBMS that is embedded with the programs and apps that use it. Db4o is highly effective at avoiding object/relational impedance mismatch, which is when technical difficulties arise in storing and accessing the data. It is also popular because the data class model can automatically define the data structure, saving time for manual modelling.

ObjectBox

These days ObjectBox has many offerings, but what they all have in common is that they excel at being speedy DBMS. ObjectBox also offers one of their original OODBMS out there. It is especially held in good regard for working very well with mobile devices as well as Internet of Things (IoT) devices which let used to analyze data use. 

InterSystems Cache

Made by InterSystems, which also makes rapid application and integration systems, InterSystems Cache is another object-oriented DBMS. You can use this one with object-oriented or SQL coding as well, and it also employs some elements of hierarchical data structures. InterSystems Cache is popular with the financial industry, as well as with governments.|
 

NoSQL databases

Finally, we have the NoSQL DBMS. The most obvious thing here is that this does not use structured query language like relational databases do, like, for example, with table-based databases. Instead, NoSQL is used to store data in a more horizontal structure. This type of NoSQL database utilizes components in its management system, like graphs, documents, and key values.

NoSQL is increasingly popular with big data databases and time series databases, meaning not only the quantity of data but the velocity at which new data must be entered into the system. For this reason, it is also excellent at dealing with real-time data modifications.   

Different types of database systems that fall under NoSQL DBMS 

Unlike relational databases, hierarchical databases, network databases, and object-oriented databases, NoSQL database types can more easily be broken down into subtypes, with each having many proprietary apps that service them. 

Document databases

The first main type of NoSQL is the document-oriented database or document store, and it is one of the simplest. It functions very well with only semi-structured data, which means there is little distinction between data and the schema for separating it. With document databases, one often needs an internal structure within each document, and this facilitates tasks like metadata extraction. This also means that for every document in the database, there can be different structures, making it highly different from relational systems. 

Key-value stores

Key-value database NoSQL systems specialize in what we know as data arrays, which are data structured based on associative maps, tables, or symbols, sometimes known as dictionaries. Again, unlike relational structures, key-value systems use data as if each record is a single and unified opaque system unto itself. One advantage here is that key-value DB systems use less computing memory to run and are favoured for flexibility and scalability.

Column-oriented databases

Column databases are sometimes referred to as wide-column stores. This is the one form of NoSQL that may appear like a relational system because it uses tables, rows, and columns. However, it has its differences. The names and formats of the columns are adaptable, meaning that the data represented can change its attributes from row to row. Some consider the column-oriented database as a two-dimensional version of the key-value structure. 

Graph databases

As the name suggests, these are graphical database structures that use NoSQL. It works by applying semantic queries to things called nodes and edges, with the former being unit of data and the latter being the lines that connect them. There are two commonly talked about forms of graphical NoSQL databases. 

The first is labeled-property graphs, which are graphs that assign easily understood labels to edges and integers. The other kind is RDF or resource description framework. This one places added information by adding extra data nodes on the graph and has arcs instead of labeled edges. RDF is better at handling longer data descriptions. 

Our conclusion about the different kinds of databases

As you can read here, when we talk about the kinds of database systems, there is a bit of a grey area between database types and database management system types. On top of that, things can get extra confusing when we throw in the DBMS software that handles the various structures and consider connections between different data in novel ways. 

Overall, the main thing to know is the difference between SQL, which includes relational, hierarchical, and network databases, with NoSQL, which includes documents, graphs, columns, and key-value databases. Of course, there are clear distinctions between things like centralized vs distributed databases. For example, as with a distributed database, the data is accessible through a variety of servers instead of storing it all within one single machine. What's more, there is a big difference between commercial databases and open-source ones.

Our final takeaway is that knowing the types of databases between SQL and NoSQL is not an easy topic in itself, even if most databases are simple. But thankfully, there are great software solutions that take over a lot of the complicated work, from one single data point to petabytes of data.

FAQs

Which type of database model connects data in different files through the use of a key field?

The type of database that connects data in different files through a key file is a relational database. Relational databases take data and place it on tables with rows and columns to organize it. With relational databases, one can also use multiple tables and connect the data between them.
 

What is the most common type of database?

The most common type of database is a relational database model. Relational databases are simple to set up, add data, submit data queries, and modify data at the same time. This is so because of the relational use of tables, rows and columns, and key fields.
 

What are the most common database objects?

There are many database objects, and the most common database objects are tables, forms, queries, reports, models, and macros. However, database objects are not limited to these six. You also need to consider things like constraints, triggers, concepts, and indexes. Different DBMS use different sets of objects.