Best Relational Databases: User Reviews from August 2024

What is Relational Databases Software?
What are the Common Features of Relational Databases?
What are the Benefits of Relational Databases?
Who Uses Relational Databases?
Challenges with Relational Databases
Which Companies Should Buy Relational Databases?
How to Buy Relational Databases
What Does Relational Databases Cost?
Relational Databases Trends

Learn More About Relational Databases

What is Relational Databases Software?

Relational databases organize and maintain data in the form of tables that are by rows and columns, where columns represent a single type of data (e.g., an order date), and rows relate to multiple data types to a single, unique identifier. Each row’s unique identifier is called a primary key. In relational databases, multiple tables can be connected using foreign keys. This allows users to search for a range of interconnected data with ease. Relational databases software facilitates the creation, maintenance, and usage of these tables. These solutions store large volumes of data and allow access to structured data sets efficiently and flexibly.

Relational databases can also be called relational database management systems (RDBMS) or structured query language (SQL) databases. An RDBMS is based on SQL that allows users to update, query, and administer a relational database. SQL is typically the standard programming language used to access a relational database. Relational databases software can read SQL and use SQL syntax or similar. SQL’s syntax is very simplistic, and as such, it is one of the easiest programming languages to access and query relational databases.

What Types of Relational Databases Software Exist?

From a licensing point of view, relational databases can be categorized under two important types:

Open-source databases

Open-source software make their source code available for anybody to access. The code is open and free for download and modification.

Commercially supported databases

Commercial or proprietary software is solely owned by the entity that developed it. It is made available only under license.

Relational databases can be deployed on both cloud and on-premises as far as the buyer complies with the license:

Cloud

A relational database deployed on the cloud provides an improved infrastructure that lets companies focus more on their strategic work rather than managing a full house of servers on-premises. These solutions provide cost control as organizations pay for what they use.

On-premises or license

An on-premises data warehouse software lets organizations buy one time, deploy in-house and enable control over their hardware and software infrastructure. This deployment solution requires a consultant to help with installation and ongoing support. One advantage of on-premises relational solutions is that it gives complete control and access over the data within an organization, helping minimize security risks.

What are the Common Features of Relational Databases?

The following are some core features within relational databases that can help users store, organize and maintain large data sets at the same time query data using a structured query language:

Data storage: Allows data to be stored in the form of tables (i.e., rows and columns). It also facilitates a primary key, which helps in the unique identification of the rows.

Data modification: Allows data update and access to multiple data elements simultaneously. Users can also retrieve data from large volumes of datasets stored in the database using a structured query language.

Database creation and maintenance: Quickly create brand-new relational databases and modify them with ease.

Indexing: This feature helps build relationships between data elements via keys and indexes which enables users with ease to access and search the databases.

Scalability: Relational database solutions grow with data, so the only capacity that’s concerning is physical or cloud storage capacity.

Data security: Relational database solutions include data security features to protect the data a business stores in its databases.

Access control: Relational databases grant administrators complete control over who can access them. Users can be granted access based on their work and requirements.

OS compatibility: Relational database solutions are compatible with numerous operating systems, so the user won’t have to worry about the OS when creating databases.

Recovery: Whether a database needs to be rolled back or outright recovered, some relational database solutions offer recovery features.

Multi-user access: RDBMS solutions allow multiple users to access databases at a single time. This functionality prevents multiple users from colliding with each other when making updates and also blocks access to partial data entries.

Other Features of Relational Databases: Open source, Proprietary

What are the Benefits of Relational Databases?

RDBMS solutions are built on a specific relational data model which makes it easy for users to access, update and retrieve data from various data sets within the database. This software can help organizations manage large volumes of data sets at the same time and give them the ability to manipulate and maintain them.

Data association: Relational databases are extremely powerful for storing and retrieving associative data. Be it e-commerce order details, patient information, stock tracking, or something more, relational databases excel in creating meaningful connections between a primary key and the related description. Since they can be uniquely generated, primary key values are typically numbers, and values (e.g., full name, quantity, order date) are associated with that value by being stored in the same row on the table. This massively improves data organization for companies.

Targeted query results: By using relational database software, businesses can build vast, interconnected databases that quickly return important information, exactly as needed. Relational databases have massive strength in being able to produce query results that span over numerous tables. By using join operations and table aliases, users can query across several tables at once to build an output of the exact data they require. This eliminates the need to store huge quantities of data on a single table. Instead, database administrators can build out as many tables as needed to better organize data, and those tables can be connected by foreign keys if any of the data needs to be associated.

Ease of use: Relational databases are designed to be easy to build and even easier to use. At a fairly low learning curve, anyone that could make use of relational databases tools would be able to do so with basic training on the software.

Data consistency: RDBMS is based on the ACID (Atomicity, Consistency, Isolation, and Durability) model which facilitates structured and consistent data sets.

Speed: The tabular format of relational databases allows quick data retrieval. The standard SQL language used to pull data from databases enables faster data pull.

Better decision-making: Relational databases facilitate the provision of well-organized data which is up to date as well. This helps organizations make accurate and timely decisions.

Who Uses Relational Databases?

Database administrator: DBAs work towards maintaining the performance and managing the database and the applications connected to them. They are also responsible for the security and integrity of the database as well as any related troubleshoot issues.

Developers: Developers write codes in various programming languages to interact with databases. They are also responsible for designing and developing new databases.

End users: They are individuals who perform data manipulation tasks on the databases like update, delete, and more.

Software Related to Relational Databases

Related solutions that can be used together with relational databases include:

NoSQL databases software: As noted previously, while relational databases solutions excel with structured data, NoSQL databases like object-oriented, document, graph, etc., more effectively store loosely structured and unstructured data. NoSQL database solutions pair well with relational databases software if a company deals with diverse data that can be collected by both structured and unstructured means.

Data warehouse software: Data warehouse software acts as a single central repository of integrated data from multiple disparate sources that provides business insights with the help of BI Tools. Data warehouses also store data similar to relational databases but the end purpose involves the collection and storing of historical data to perform reporting and data analysis.

Data quality software: Relational databases struggle with handling unstructured data, and duplicate or incorrect data can throw off the accuracy of results once data becomes structured. Data quality solutions help clean and structure data, which makes it easier to turn around and create a formal relational database for that data.

Challenges with Relational Databases

Software solutions can come with their own set of challenges.

Unstructured data: As noted above, there is a point where relational databases can struggle: handling unstructured data. Relational databases hinge on data being structured to properly create relationships between data points and data tables. If a company uses mostly unstructured data, they should consider perhaps a NoSQL database solution or a data quality software to clean and structure unstructured data.

Query lag: Relational databases can store massive quantities of data, but they run queries a little more slowly on larger data sets. This is mainly due to the sheer volume of data being queried. In situations where queries might traverse significant quantities of data, users can try to query based on specific values whenever possible. Also, querying strings takes significantly longer than querying numerics, so focusing on numerics whenever possible may help improve search times.

Which Companies Should Buy Relational Databases?

What makes relational databases software particularly beneficial is that it’s highly flexible and can be used by many teams throughout a company. Below are some examples:

Finance and accounting: Relational databases can be used to track payments and dues by associating a vendor ID, customer ID, or other unique identifiers to payment dates, payment amounts, check or order numbers, and more. All of this can be easily queried through relational database tools, and a complete transactional record can be created in a matter of minutes or even seconds. The ability to organize or isolate this data by, say, transaction date or personnel can greatly improve efficiency.

E-commerce: Internet prevalence and ease of use has made online ordering, from food to clothes or machinery, not only simple but very widely used. Relational databases can store vast transactional data, including order date/time, customer name, payment method used, customer location, and more. Verifying an order’s correctness is a query away. Additional benefits for e-commerce come in that relational databases can store incredible volumes of information. Individual tables can store millions upon millions of entries at once without harming workflow.

Healthcare: Relational database tools offer immense value in health care because of the ability to relate so many data points to a single unique identifier. In health care, patients have a number of data points to describe their condition, including age, weight, blood pressure, and others. By being able to associate all of those data points to a single unique identifier (e.g., a person’s patient ID), health care professionals—doctors, nurses, lab techs, database admins, and more—can have quick access to any relevant data.

How to Buy Relational Databases

Requirements Gathering (RFI/RFP) for Relational Databases

If a company is just starting and looking to purchase their first relational database solution, or maybe an organization needs to update a legacy system--wherever a business is in its buying process, G2.com can help select the best relational database software for the business.

The particular business pain points might be related to storing and managing large volumes of data sets within an organization. If the company has amassed a lot of data, the need is to look for a solution that can help organize and structure that data to manage it. Users should think about the pain points and jot them down; these should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees who will need to use this software, as this drives the number of licenses they are likely to buy.

Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist serves as a detailed guide that includes both necessary and nice-to-have features including a budget, features, number of users, integrations, security requirements, cloud or on-premises solutions, and more.

Depending on the scope of the deployment, it might be helpful to produce an RFI, a one-page list with a few bullet points describing what is needed from a data warehouse software.

Compare Relational Databases Products

Create a long list

From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor.

Create a shortlist

From the long list of vendors, it is helpful to narrow down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, businesses can produce a matrix to compare the features and pricing of the various solutions.

Conduct demos

To ensure the comparison is thoroughgoing, the user should demo each solution on the shortlist with the same use case and datasets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition.

Selection of Relational Databases

Choose a selection team

Before getting started, it's crucial to create a winning team that will work together throughout the entire process, from identifying pain points to implementation. The software selection team should consist of members of the organization who have the right interest, skills, and time to participate in this process. A good starting point is to aim for three to five people who fill roles such as the main decision maker, project manager, process owner, system owner, or staffing subject matter expert, as well as a technical lead, IT administrator, or security administrator. In smaller companies, the vendor selection team may be smaller, with fewer participants multitasking and taking on more responsibilities.

Negotiation

Just because something is written on a company’s pricing page, does not mean it is final (although some companies will not budge). It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to give a discount for multi-year contracts or for recommending the product to others.

Final decision

After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. If the tool is well used and well-received, the buyer can be confident that the selection was correct. If not, it might be time to go back to the drawing board.

What Does Relational Databases Cost?

There are a couple of robust relational databases that are available for free in the market. There are typically two pricing models, one where users pay only for what they use, and in the other one, users pay a one-time license fee.

Relational Databases Trends

Databases and data aggregation

The debate continues on the use of relational databases solutions versus NoSQL databases as the better business solution, as data aggregation continues to rise in the business world. Data-driven products and services require immense data backing now, and the debate is on the best way to store that data. In reality, the two database types should be used together. While relational databases excel in structured data storage, NoSQL databases—non-relational databases—shine when there’s no real structure to how data should be collected and stored. Both relational and non-relational databases can scale quite easily, given the right software supporting them. This shouldn’t be a debate, but a collaboration. Thus, bridging the gap between SQL/NoSQL to let them work together.

Big data

Data has become the backbone of conducting business in the information age. As data drives business decisions and trends, the data must be digestible, easy to follow, and easy to reference. That’s why big data software mostly falls back on relational database solutions. Designed with strict organization, referencing, and referral in mind, relational databases can absorb and store massive amounts of data to be later digested in the decision-making process.

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