Plz tell about this
Lack of scalability: Relational databases can struggle with scalability as the data grows in size and complexity. Performance issues: Join operations and complex queries can lead to slower performance in relational databases. Data redundancy: Normalization in relational databases can result in storing data in multiple tables, leading to redundancy and inefficiency.
Advantages of using a database include efficient data organization, easy data retrieval, and data security. However, disadvantages can include high initial setup costs, potential for data redundancy, and complexity of managing and maintaining the database system.
Data redundancy
Some disadvantages of the hierarchical database model include complexity in representing certain types of relationships, limited flexibility in querying data due to its rigid structure, and potential data redundancy issues as each child can only have one parent record.
This statement is incorrect. Data redundancy refers to storing the same piece of data in multiple places, leading to inefficiency and inconsistency. A group of related fields is known as a database or a record in a database.
with data redundancy there willbe more wastage of memory space as same type of data willbe saved many times when to want to see the data all duplicate results will come
controlling data redundancy
Redundancy means duplicacy of data or repetitive data. In distributed database case the data is stored in different systems . So the answers is yes there can be redundancy of records / data.In distributed database , data is stored in different systems. Since the data is distributed there is redundancy of records.
Data redundancy Lack of data redundancy Data inconsistency Data security
Duplication of data is data redundancy. It leads to the problems like wastage of space and data inconsistency.
coding redundancy interpixel redundancy psycovisual redundancy
one is a validation the other is redundancy clue is in the name
Data redundancy means storage of data.
In database we store data however the can be redundant. Redundancy means repetitive data that is taking extra storage space . So to reduce or prevent the storage space we should eliminate redundancy or just reduce it.
Data redundancy: Sometime Data redundancy refers to in computer data storage, is a property of some disk arrays which provides fault tolerance, so that all or part of the data stored in the array can be recovered in the case of disk failure. The cost typically associated with providing this feature is a reduction of disk capacity available to the user, since the implementations require either a duplication of the entire data set, or an error-correcting code to be stored on the array.Redundancy is attained when the same data values are stored more than once in a table, or when the same values are stored in more than one table.One of the biggest disadvantages of data redundancy is that it increases the size of the database unnecessarily.
An example of data redundancy is when the same information is stored in multiple places in a database. For example, if customer addresses are stored in both an "order details" table and a "customer information" table, it creates redundancy. This redundancy can lead to inconsistencies if the data is not properly maintained.
Lack of scalability: Relational databases can struggle with scalability as the data grows in size and complexity. Performance issues: Join operations and complex queries can lead to slower performance in relational databases. Data redundancy: Normalization in relational databases can result in storing data in multiple tables, leading to redundancy and inefficiency.