Data Modeling in NoSQL Databases
In comparison to relational databases, the data modeling for the non-relational (or NoSQL) databases is rather different because of the possibility of having flexible schema and working with various data structures. As to the leading models of NoSQL databases, they widely use the following approaches, among others.
- Document-Oriented Modeling: Different data entities and the attributes which are required can be represented by documents (ex: JSON, XML), which is aimed for complex data such as semi-structured or unstructured data.
- Key-Value Modeling: Simple key value storage model which takes less time to perform simple retrieval operations but it may not be able to handle complex querying.
- Graph Modeling: Refers to the representation of data as a graph structure, where entities (nodes) are connected by relationships (edges) to form a network of interconnected data.
Data Modeling in System Design
Data modeling is the process of creating a conceptual representation of data and its relationships within a system, enabling stakeholders to understand, communicate, and implement data-related requirements effectively.
Important Topics for Data Modeling in System Design
- What is Data Modeling?
- Importance of Data Modeling in System Design
- Types of Data Models
- What are Entities, Attributes, and Relationships?
- Data Modeling Notations
- Normalization Techniques
- Denormalization Strategies
- Data Modeling in NoSQL Databases
- Time Series Data Modeling
- Real-world Examples of Data Modeling
- Best Practices for Data Modeling
- Benefits of Data Modeling
- Challenges of Data Modeling
Contact Us