1) While data holds immense value, not all of it must occupy space in the active database. In an era of decreasing computing and storage costs, adopting a ‘less is more’ approach. Archive and retain only the essential data.
2) Indexes: Properly designed indexes can speed up data retrieval. Indexes help locate specific rows efficiently, especially when searching large datasets.
3) Utilizing Object-Relation Mapping (ORM) allows applications to handle complex queries and relationships more efficiently.
4) When fetching large result sets, unbuffered mode reduces memory consumption by fetching rows one at a time
The statement that "Utilizing Object-Relation Mapping (ORM) allows applications to handle complex queries and relationships more efficiently" is not entirely accurate. While ORM tools do simplify the interaction between object-oriented programming languages and relational databases, they can sometimes be less efficient than writing SQL directly, especially when dealing with complex queries. This is because ORM tools generate SQL queries automatically, which may not always be as optimized as those written by a skilled SQL developer. Additionally, some ORM tools may not support advanced SQL features, limiting their effectiveness for certain applications .
ORM tools provide a higher level of abstraction, allowing developers to work with objects and their relationships instead of directly writing SQL. This abstraction can make development faster and more intuitive, as developers can use the programming language's syntax to interact with the database. However, this abstraction can also introduce performance overhead, as the ORM tool needs to translate object-oriented operations into SQL queries. This translation process can result in less efficient queries and potentially more database queries than necessary, which can slow down performance .
In summary, while ORM tools can significantly simplify database interactions and reduce the amount of SQL code developers need to write, they may not always provide the same level of efficiency as hand-written SQL, especially for complex queries and operations. Developers should consider the specific requirements of their application, including performance needs, when deciding whether to use an ORM tool .
1) While data holds immense value, not all of it must occupy space in the active database. In an era of decreasing computing and storage costs, adopting a ‘less is more’ approach. Archive and retain only the essential data.
2) Indexes: Properly designed indexes can speed up data retrieval. Indexes help locate specific rows efficiently, especially when searching large datasets.
3) Utilizing Object-Relation Mapping (ORM) allows applications to handle complex queries and relationships more efficiently.
4) When fetching large result sets, unbuffered mode reduces memory consumption by fetching rows one at a time
Ask the DB administrator for help !!
The statement that "Utilizing Object-Relation Mapping (ORM) allows applications to handle complex queries and relationships more efficiently" is not entirely accurate. While ORM tools do simplify the interaction between object-oriented programming languages and relational databases, they can sometimes be less efficient than writing SQL directly, especially when dealing with complex queries. This is because ORM tools generate SQL queries automatically, which may not always be as optimized as those written by a skilled SQL developer. Additionally, some ORM tools may not support advanced SQL features, limiting their effectiveness for certain applications .
ORM tools provide a higher level of abstraction, allowing developers to work with objects and their relationships instead of directly writing SQL. This abstraction can make development faster and more intuitive, as developers can use the programming language's syntax to interact with the database. However, this abstraction can also introduce performance overhead, as the ORM tool needs to translate object-oriented operations into SQL queries. This translation process can result in less efficient queries and potentially more database queries than necessary, which can slow down performance .
In summary, while ORM tools can significantly simplify database interactions and reduce the amount of SQL code developers need to write, they may not always provide the same level of efficiency as hand-written SQL, especially for complex queries and operations. Developers should consider the specific requirements of their application, including performance needs, when deciding whether to use an ORM tool .
Absolutely .. thanks for adding more clarity ..
AI convinced me with this, I haven't tested it my self tho 🤷♂️.
hence the slate statement ask the DBA :-D...
Those were from my experience.. Always had DBA and senior developers who had guided or helped me to explore the options
Bulk data operations and for fine tuning an performance based query ORM might not work.
Yes, so I like orm like hibernate or drizzle. They also provide the manual way to construct SQL query.