There are several types of databases, and their differing designs process data in different ways. Providing access to information is the primary purpose of a database. They can be used for a variety of tasks, ranging from storing photos to buying items online to analyzing marketing and sales data. Large amounts of information can be stored in databases in organized, easily searchable ways.
Organizations will use different databases, depending on the type of data and the organization’s goals.
Database management systems (DBMSs) can be described as the software that supports communication between humans and the database. (The term “database” loosely refers to the database management systemand any software that is associated with the database.) The DBMS is a necessary part of the database.
A variety of databases have been developed over the years, and each design comes with its own limitations and strengths. Understanding the different types of databases is crucial when selecting one to support the organization’s goals. Databases support a business’s growth in numerous ways, including the following:
- Efficiently stores and retrieves data
- Used to analyze business data
- Supports the development of business intelligence and making informed business decisions
- Collects and stores crucial customer data
- Supports queries that can be used for a variety of research purposes
Generally speaking, a database stores and provides access to a collection of data. A “query” describes the act of retrieving data from a database. This function allows researchers to access information or alter the data, such as deleting or adding information.
Familiarity with a technology is a good thing. When a piece of computer technology and its software are well understood, the system can be used to maximum efficiency, and it is less likely there will be surprises.
However, technologies change and evolve, and there comes a time when the old, comfortable, well-understood computer system is no longer compatible with current software systems and platforms. It has become a “legacy system.”
The inexpensive software and storage offered by the cloud is normally extremely efficient (compared to legacy systems) and, occasionally, cutting-edge. (Compared to a legacy system, it may all seem to be cutting-edge.)
The cloud has become an extremely useful tool, especially for doing business over the internet, and is considered the biggest shift in business models in the last few decades.
Unfortunately, the cloud rarely works well with legacy systems. Legacy databases that were initially designed for on-premises installations and to support a small user base cannot support the dynamic environment offered by the cloud.
While it is possible for a legacy system to continue being efficient because it supports a niche, generally speaking, many older organizations have replaced their databases to stay (or become) competitive.
10 Types of Databases and Their Uses
Regardless of the design, databases typically have the goal of organizing data into patterns and structures so that the data can be located and accessed easily. Several different types of databases have been developed over time, and modern designs are based on unique solutions, and the growing need to meet legal requirements and regulations.
The type of database selected will have a significant impact on the kinds of operations your business can perform easily, how the data is perceived, and the services it offers.
Historically, relational databases became the dominant, most popular database in the 1980s (and are still extremely popular). They organize the data in rows and columns within a series of tables. Relational databases traditionally use structured query language (SQL) for querying or writing data. In the 2000s, NoSQL became popular as an alternative option that supported “big data research.”
A startup may need to decide what kind of database will best serve its present and future needs. In some cases, it may need different kinds of databases for different tasks. (Use of multiple databases should be considered as an option.) Listed below are some popular types of databases.
- Open-source databases: This type of database is designed for public use and is free. The term “open source” normally refers to software and platforms that allows users to see how the program was written and constructed. Open-source products can be modified to suit the needs of the user. (Some businesses improve on them, and then charge for the improved version.)
- Relational databases: With relational databases, the integrity of the data is a priority, but scalability is not. Because of their maturity – over 40 years old – relational databases have become very user-friendly, and an extremely large number of tools have been developed to support them.
- NoSQL databases: This type of database stores data using an unstructured, or non-relational system. The lack of a structured system allows NoSQL to process much larger amounts of data than SQL systems, and the design typically allows for easy expansion of the data’s storage.
- Commercial databases: These types of databases are designed by a commercial business, which then sells or rents the database to its customers. They can vary dramatically in design and purpose, with some being standardized, and some being unique. (Commercial databases can also mean databases that are filled with researchable data, and are available to the public.)
- Distributed databases: With a distributed database, data is spread out over several devices, each with its own database. Data is not stored on a single device. The benefits of these databases include improved speeds and greater reliability. Security is one of their weaknesses.
- Centralized databases: These differ dramatically from distributed databases. A centralized database operates entirely from a single location. Larger businesses or universities generally use this type of database, which is located within a central computer.
- Graph databases: This type of database is designed to show the relationships that exist between the data files. With graph databases, these relationships are stored within the database “with” the original data. This system is extremely efficient, and when the goal is managing these connections, it is faster.
- Cloud databases: These are cloud services that are accessed through the internet. Cloud databases offer many of the same services as on-premise databases, but with the additional flexibility of cloud computing.
- Object-oriented databases: In this design, data is expressed as objects and classes. An object represents a piece of information – a name or phone number, while a class is a group of objects (similar to a file). Object-oriented databases are normally more efficient than relational databases and are often used with CAD/CAM modeling systems, document management systems, and geographic information systems.
- Operational databases: These databases are designed with the purpose of modifying data in real time. Operational databases are extremely useful for business analytics. They can be based on relational or NoSQL databases, depending on the organization’s needs.
Online Transaction Processing (OLTP) vs. Online Analytical Processing (OLAP)
Online Transaction Processing (OLTP) is a version of data processing that can execute a variety of transactions occurring simultaneously – examples include shopping, online banking, or sending text messages. These databases often contain large amounts of data that can be refined into business intelligence. However, these databases were not designed for analysis.
Online Analytical Processing databases (OLAP), on the other hand, are designed for analysis and are used when analyzing business data. For purposes of analysis, organizations can collect and store data taken from a variety of sources, such as their own business transactions and internal systems, smart meters, and other websites.
Selecting the Right Types of Databases
The more well-known clouds (AWS, Google, Microsoft) offer a selection of databases, which can be used as needed. While this situation allows for using different databases without making a significant investment, selecting the wrong database is still a waste of money.
Taking the time to research, discuss, and think will lead to intelligent decisions about the kind of database technology that is needed. Questions to ask when selecting a database are:
- How much does it cost?
- How will the data be used – research (OLTP), real-time sales decisions (OLAP), both?
- What type of database is most effective for the organization’s goals (NoSQL for broad research, SQL for day-to-day processes, graph databases for establishing relationships, etc.)?
- How difficult (or easy) is it to access the data?
- How quickly is data processed?
The type of database that is selected will have an impact on the processes and projects of your organization. A permanent, or semi-permanent database should not be purchased or leased based through the use of intuition or flashy gimmicks. (Intuition should be used when there is minimal information to work with, or when there is a strong sensation that something is wrong.)
Thorough research pays off – it supports improved decision-making and provides a better understanding of the database technologies currently available. It is important to research the business software you’re paying for, preferably before you pay for it.
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