MultiValue Database


A MultiValue database is a type of NoSQL database management system that stores data in a multidimensional structure, allowing multiple values to be associated with a single key. It is particularly well-suited for applications that require complex data manipulation and rapid querying. This database model is often used in industries such as finance, healthcare, and retail, due to its flexibility and high-performance capabilities.

Key Takeaways

  1. MultiValue Database is a type of NoSQL database that stores information in a multidimensional schema, allowing for complex data structures and multiple relationships between data items.
  2. This database model is particularly efficient in managing tasks involving large amounts of data and processing intensive workload, as it allows easy access and manipulation of data with a more intuitive representation.
  3. MultiValue Databases are widely used in industries like finance, retail, healthcare, and telecommunications, thanks to their flexibility and the ability to handle high transaction volumes with minimal lag or latency issues.


The term “MultiValue Database” is important in the technology world as it refers to a specific type of NoSQL database management system (DBMS) that enables efficient storage, management, and retrieval of data, consisting of both key and multi-valued attributes.

This database model offers flexibility, speed, and scalability, allowing multiple values to be associated with a single key while supporting simple and rapid application development.

Its design ensures reduced data redundancy and seamless integration with various applications, making it a popular choice across diverse industries.

By utilizing the nested structure of MultiValue Databases, organizations can streamline complex data relationships, enhance productivity, and ensure a more proficient data handling process in the ever-evolving technology landscape.


MultiValue Database technology serves as an effective and flexible solution for organizations that handle large volumes of data with complex relationships. The primary purpose of a MultiValue Database system is to streamline and simplify the management of intricate data structures in various industries, such as retail, finance, healthcare, and telecommunications.

By using a multi-dimensional data model, it allows the storage and organization of information in a way that mirrors real-world relationships among the data elements. This approach results in quicker data retrieval and efficient processing, ultimately leading to better decision-making and overall operational efficiency for businesses relying on vast amounts of data.

Moreover, MultiValue Databases are known for their scalability and adaptability, making them a strong choice for organizations that experience rapid data growth or whose data requirements evolve over time. These databases cater to the needs of businesses requiring agile data management to meet their changing market demands, offering a reduced cost of ownership and uncompromised performance as their data needs grow.

A key advantage of MultiValue Database systems lies in their ability to seamlessly integrate with various legacy systems and modern applications, providing a robust and future-proof data management solution that can evolve in alignment with the ever-changing needs of the digital landscape.

Examples of MultiValue Database

A MultiValue database, also known as a multi-dimensional database, is a type of NoSQL database that allows each data record to contain more than one value for individual fields, making it extremely efficient for storing complex data structures and relationships. Here are three real-world examples of MultiValue databases:

Rocket UniVerse Database:Rocket UniVerse is a MultiValue database management system by Rocket Software, utilized by industries such as finance, retail, healthcare, and manufacturing. It provides efficient data management solutions and supports multiple data models, helping businesses store and manage large volumes of intricate information. An example application is the UK’s National Health Service (NHS) using it for their Data Management System to handle patient data.

InterSystems Caché:InterSystems Caché is another example of a MultiValue database that has high-performance and built-in support for SQL access. It is used across various industries like healthcare, finance, and telecommunications. A real-world example is Epic Systems, a healthcare software company, utilizing InterSystems Caché as their underlying database management system to manage Electronic Health Records (EHR) and patient data across many hospitals and healthcare organizations.

jBASE Database from Zumasys:jBASE is a MultiValue database system designed for scalability, reliability, and interoperability with other databases. Its wide range of applications include retail, financial analytics, and manufacturing, to name a few. An example of jBASE’s implementation is Ladybridge Systems Ltd., a UK software company, using jBASE for their OpenQM product to deliver cost-effective and flexible solutions to clients, such as logistics providers, for accessing and managing large datasets.

MultiValue Database FAQ

What is a MultiValue Database?

A MultiValue Database is a type of NoSQL database that uses a specific data model called the MultiValue data model. It stores data as lists or tables instead of traditional rows and columns. This makes it efficient for handling complex data types and relationships.

What are some advantages of a MultiValue Database?

Some advantages of MultiValue Databases include the ability to handle large amounts of complex data, reduced storage requirements, and efficient querying capabilities. They are suitable for applications that require flexibility in data design and the processing of hierarchical data structures.

How does a MultiValue Database differ from a traditional relational database?

A MultiValue Database differs from a traditional relational database in the way it organizes and stores data. Instead of storing it in Table with rows and columns, A MultiValue Database stores data as lists and associative arrays, which allows for multiple values within a single field. This provides greater flexibility for handling complex data structures and better performance for specific use cases.

What are some popular MultiValue databases?

Some popular MultiValue databases include Rocket UniData, Rocket UniVerse, InterSystems Cache, OpenQM, and Revelation Software’s OpenInsight. These databases offer varying features for different application needs and cater to various industries such as finance, healthcare, and retail.

What industries typically use MultiValue Databases?

Industries that typically use MultiValue Databases include finance, healthcare, retail, and manufacturing. Due to their ability to handle complex and large amounts of data, MultiValue databases are also suitable for applications that require the processing of hierarchical data structures and analytics.

Related Technology Terms

  • Associative Arrays
  • Dimensional Modeling
  • Query-by-Example (QBE)
  • Entity-Attribute-Value (EAV) model
  • Pick Operating System

Sources for More Information

  • IBM: IBM is a multinational technology company with extensive experience in the MultiValue Database field. They offer several solutions, including the IBM U2 family of MultiValue Database products.
  • Rocket Software: Rocket Software is a global software development firm specializing in modernizing legacy systems and applications. Their MultiValue Database solutions include UniData, UniVerse, and D3.
  • Pick Cloud Inc.: Pick Cloud is a cloud hosting and services provider exclusively focused on MultiValue Databases. They provide cloud-hosted solutions, consulting, and support for a variety of MultiValue Database platforms.
  • Bluefinity International: Bluefinity International is a software development company specializing in application development and integration tools for MultiValue Databases. Their flagship product, Evoke, is a development platform designed to create web and mobile apps using existing databases.

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