In this article we are going to discuss about what is graph data modelling and what it entails,benefits of graph data modelling and some of the common mistakes we can avoid when data modelling
What is Graph Data Modelling (Relational Database)?
Data modeling refers to constructing a logical data model from a given concept. In order to organize a logical data model, we need to understand the core of a database first. Creating an efficient model in terms of function and performance based on that understanding comes after. This includes the work process of returning to a physical database model and reflecting it in the database of a specific information system according to the customer’s needs.
First step of data modelling is to accurately analyse the subject of the content that define the system.The second is to build an actual database with the analyzed model and use it for development and data management.
What Are the benefits of data modelling
Enhanced Data Security:
Data modelling can help to enhance data security by identifying and mitigating data security risks. For example, a data model can be used to identify sensitive data and implement appropriate security controls.
Efficient data integration:
Data modelling facilitates the integration of disparate data sources, ranging from databases to spreadsheets. This helps organisations streamline their processes, eliminate data silos, and improve operational efficiency.
Increased agility and scalability:
As businesses grow, so does the volume of data they handle. Data modelling allows organisations to design scalable database architectures by making it easier to update database systems and applications.
After understanding what is data modelling and what are some of the benefits of data modelling we are now going to focus on what are some of the mistakes we have to avoid when data modelling in graph database in Apache AGE
Common Mistakes To Avoid when when designing a graph data model Apache AGE
Not using the correct node type: AGE supports two types of nodes: property nodes and label nodes. Property nodes are used to store data, while label nodes are used to classify nodes. Be sure to use the correct node type for each node in your graph.
Not using the correct relationship type: AGE supports two types of relationships: directed and undirected. Directed relationships have a direction, while undirected relationships do not. Be sure to use the correct relationship type for each relationship in your graph.
Not using the correct property type: AGE supports a variety of property types, including strings, integers, floats, and booleans. Be sure to use the correct property type for each property in your graph.
Not modeling relationships explicitly: In a graph database, relationships are just as important as nodes. When designing your data model, be sure to explicitly model all of the relationships between your nodes. This will allow you to take advantage of the graph database's ability to query and traverse relationships.
Conclusion
When creating graph databases especially in Apache AGE we should consider how we are modelling our data so as to ensure flexibility,scalability and also ensure that the database can be able to perform queries fast and provide reliable queries.
Resources:
Article on Data modelling:
[https://medium.com/agedb/what-is-data-modeling-part-2-849d978b076f]
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