Structured VS Unstructured Database
The data present in the database will either be structured or unstructured. Let’s see both these structures,
1. Structured Database
Structured data is the data that has been predefined to a set structure (table) before being placed in data storage.
- There are many ways to store structured data, but The best example of structured data is the relational database (RDBMS)
- It is used where a record is required in the form of a structure or table, i.e., universities, schools, ticket data, etc.
- Almost 10% of structure data are used nowadays
- It is our main topic in the database syllabus.
- schema-on-write is another name for a structured database.
2. Unstructured Database
Unstructured data is stored in its native (actual) format as it is sent. So, Data has no proper structure when it is stored in a database and is not processed until it is used.
- It comes in thousands of file formats, including email, social media posts, presentations, chats, satellite imagery, etc.
- NoSQL (Not only SQL) database software is most suitable for this purpose
- Most technologies are using unstructured data. Almost 90% of the database is unstructured. Big data using an unstructured database
- Schema-on-read is another name for an unstructured database.
Advantages of Unstructured data
As there are pros and cons of structured data, unstructured data also has strengths and weaknesses for specific business needs. Some of its benefits include:
- Freedom of the native format: Because unstructured data is stored in its native format. So, the data is not defined until it is needed.
- Faster accumulation rates: There is no need to predefine the data, which means it can be collected quickly and easily.
- Massive data storage: It can hold massive amounts of data easily.
Keep in mind that the data In the database may be in any of the following forms.
- And others
According to need, all the above database forms may be either structured or unstructured.
Note: The earliest types of database management systems consist mainly of hierarchy and network models. However, over time, these models became overtaken by relational databases.