What is Network Database Management Systems: Guide to NDBMS

Table of Contents [show]

Introduction

The article talks about Network Database Management Systems (NDMS), explaining how they work, their types, why they are important, and their good and not-so-good sides. It also gives examples like Integrated Data Store (IDS) to make things easier to understand. The article wants to help people understand network databases by talking about both the good parts and the challenges.

What is a Network Database Management System(NDMS)?

The network model in databases shows data as connected records in a graph. It's made to fix problems with the hierarchical model. Records link with pointers, creating a network. Each record can have many parents and children, allowing flexible connections. The network model is flexible, unlike the strict hierarchical model, which makes it easier to organize complex relationships.

Types of Network Databases

There are mainly 4 types of Network Database Management Systems, which are as follows:
 

• Integrated Data Store (IDS): Integrated Data Store (IDS) is a special way to organize information on computers. It connects data like pieces in a puzzle, letting them have flexible relationships. Lots of people used Integrated Data Stores (IDS) a long time ago, mostly on big computers in the 1970s and 1980s.
• IDMS (Integrated Database Management System): IDMS is a computer system that arranges information like building blocks, using a network idea. Developers created it for big mainframe computers, enabling the creation of intricate data structures by connecting them through pointers.
• TurboIMAGE: TurboIMAGE is a special computer system for HP 3000 minicomputers. It uses a network idea to organize information like connected pieces. TurboIMAGE helps flexibly manage data, making it easy to find and work with.
• Univac DMS-1100: Univac DMS-1100 is a special computer system for Univac's big mainframe computers. It uses a network idea to connect information, making relationships between data with pointers. Univac DMS-1100 helped organize and find interconnected data in the early days of managing databases.

Network DBMS Model

The network DBMS model is like a special way of organizing information. It links each piece of data to others with pointers, creating a structure like a graph. This helps make flexible relationships, like having more than one parent or child for each piece of data. The idea behind the network database management system model was to fix problems with another model called the hierarchical model. Although not used much now, it was crucial in the past and helped us manage data better.

Learners Also Read:- What is a Database Management System: Type | Applications | Examples

Network Database Structure

A network database structure is like putting together puzzle pieces in a special way. Each piece, or record, can connect to many others, making a network of relationships. This helps make flexible connections because each record can have several parents and children.

Network database management system structure was made to solve problems with the hierarchical model and make it easier to show complicated connections in a database. Even though we use different systems now, like relational databases and NoSQL databases, the network database systems structure was important in the early days of handling data. It's like a stepping stone in how we organize information in databases.

Example of Network Database

In the network DBMS example, Think of an Integrated Data Store (IDS) as a special way to organize information on big computers in the 1970s and 1980s. It connected data like puzzle pieces, showing flexible relationships. Even though we use different systems now, IDS was important in the early days of handling data. In the past, people used it as a way to organize information.

Pros and Cons of Network Database Management System

Pros:

• Flexible Relationships: It lets you especially connect data pieces, using pointers, so you can show complicated relationships between them.
• Efficient Retrieval: Good at getting connected data easily, so you don't have to do complicated joins like in other databases.
• Data Integrity: Keeps data organized and correct by making sure records are connected, which helps avoid repeating the same information.
• Hierarchical Structure: Gives data a special order, like building blocks connected, making it easy to show some types of information neatly.
• Data Independence: If you make changes to how the data is organized, it might not always affect how the programs using the data work, giving some freedom in managing data.

Cons:

• Complexity: Making the design and setup can be hard because everything is connected, which might be tricky for some people to understand.
• Scalability Issues: Making the database bigger can be hard as you add more records and connections between them.
• Lack of Standardization: When using this kind of database, there isn't as much agreement on the languages and tools you can use to ask it questions, unlike with other databases.
• Limited Adoption: More people like to use relational databases now, which means there is not as much help and knowledge available for the other kinds of databases.
• Maintenance Challenges: If you want to change how things are organized, it might need big changes, which could affect how programs work and make it harder to take care of.
• Cost: Setting up and keeping this kind of database might cost more because it's a bit harder, and there aren't as many people who know how to work with it compared to other databases that more people use.

Conclusion
 

In conclusion, Network Database Management Systems (NDMS), explain how they work, their history, and what's good and not-so-good about them. It uses examples like Integrated Data Store (IDS) and discusses the strengths, like flexible connections, and challenges, like it being a bit tricky. The article recognizes the importance of old network databases in shaping how we organize data and highlights the pros and cons of NDMS, even though they are not as popular as other types of databases like relational ones. Overall, it's a helpful guide for understanding these systems and their impact on managing data.

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