Relational Databases reviews by real, verified users. Find unbiased ratings on user satisfaction, features, and price based on the most reviews available anywhere.
Products classified in the overall Relational Databases category are similar in many regards and help companies of all sizes solve their business problems. However, small business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Small Business Relational Databases to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Small Business Relational Databases category.
In addition to qualifying for inclusion in the Relational Databases Software category, to qualify for inclusion in the Small Business Relational Databases Software category, a product must have at least 10 reviews left by a reviewer from a small business.
SQL Server 2017 brings the power of SQL Server to Windows, Linux and Docker containers for the first time ever, enabling developers to build intelligent applications using their preferred language and environment. Experience industry-leading performance, rest assured with innovative security features, transform your business with AI built-in, and deliver insights wherever your users are with mobile BI.
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases.
About IBM Db2 IBM believes in unlocking the potential of your data, not throttling it. We hold our databases to a higher standard, making it easy to deploy your data wherever it's needed, fluidly adapting to your changing needs and integrating with multiple platforms, languages and workloads. IBM Db2 is supported across Linux, Unix, and Windows operating systems.
MariaDB frees companies from the costs, constraints and complexity of proprietary databases, enabling them to reinvest in what matters most – rapidly developing innovative, customer-facing applications. MariaDB uses pluggable, purpose-built storage engines to support workloads that previously required a variety of specialized databases. With complexity and constraints eliminated, enterprises can now depend on a single complete database for all their needs, whether on commodity hardware or their
Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks such as hardware provisioning, database setup, patching and backups. It frees you up to focus on your apps so you can give them the better performance, availability, security, and compatibility they need. Amazon RDS is available on 6 familiar database instances
• Harness data with broad functionality and unlimited scalability. IBM Informix is a secure embeddable database, optimized for OLTP and Internet of Things (IoT) data. Informix has the unique ability to seamlessly integrate SQL, NoSQL/JSON, time series and spatial data. Everyone from developers to global enterprises can benefit from its reliability, flexibility, ease of use and low total cost of ownership. • Optimize business decisions Perform analytics close to data sources to enhance local dec
Knack empowers everyday innovators to easily overcome critical business challenges. By leveraging Knack’s intuitive no-code platform and expert builder network, teams can quickly build custom applications that collect and manage data, automate processes and move workflows online. Knack helps non-programmers easily build beautiful, data-driven web apps. Data can be imported from spreadsheets and converted to an online database. Tools like search, forms, and tables are used to build web apps that
The SAP HANA® platform helps you reimagine business by combining a robust database with services for creating innovative applications. It enables real-time business by converging trans-actions and analytics on one in-memory platform. Running on premise or in the cloud, SAP HANA untangles IT complexity, bringing huge savings in data management and empowering decision makers everywhere with new insight and predictive power.
Relational databases organize data in tables by rows and columns, where columns represent a single type of data (e.g., an order date), and rows relate multiple types of data to a single, unique identifier. Each row’s unique identifier is called a primary key. Multiple tables can be connected to each other using foreign keys, which are a particular column of the same type of data on two or more tables. This allows users to find vast arrays of interconnected data with ease. Relational databases software facilitates the building, maintenance, and usage of these tables.
Relational databases are not usually object-oriented, as they are built on creating relationships between pieces of data. Typically, relational databases are built on a querying language called SQL (Structured Querying Language). Relational databases software will almost always read SQL and use SQL syntax or similar. SQL’s syntax is very simplistic, and as such, it is one of the easiest languages to learn and use. Relational databases software is often built to follow the ACID (atomicity, consistency, isolation, and durability) transaction model to confirm that updates made to a SQL database are complete, accurate, and reliable.
Key Benefits of Relational Databases Software
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 its describing information. Because they can be uniquely generated, primary key values are typically numbers, and values (e.g., full name, quantity, order date) are associated to 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 a 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 in your company that could make use of relational databases tools would be able to use them with basic training on the software.
What makes relational databases software particularly beneficial is that it’s highly flexible and can be used by so 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 your finance associates’ efficiency.
E-Commerce — Internet prevalence and ease of use has made online ordering, from food pickups 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.
Patient Tracking — 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 hundreds of data points to describe their condition, including age, weight, blood pressure, and numerous 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 and all relevant data.
Database Creation and Maintenance — Quickly create brand-new relational databases and modify them with ease.
Scalability — Relational database solutions grow with your data, so the only capacity you have to worry about is physical or cloud storage capacity.
Data Security — Relational database solutions include data security features to protect the data your business stores in its databases.
OS Compatibility — Relational database solutions are compatible with numerous operating systems, so your business 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 in the event errors occur.
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 with that advantage, you may find that relational database tools 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, 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.