Database management systems are created to store large amounts of data. This could be the account information from user accounts on a social media website or a company’s customer information. Database management systems also feature different operations and functions that can be performed on stored data.
Key Takeaways
- A join in SQL combines data from two or more tables based on a related column, while an inner join returns only the rows with matching values in both tables.
- Inner join is a join operation, so all inner joins are joined, but not all joins are inner.
- Other types of joins include outer joins (left, right, and full) and cross joins, which return different results than inner joins.
Join vs Inner Join
The difference between Join and Inner Join is that the Join keyword is used to combine two sets of values, and there are four types of join, namely Inner Join, Outer Join, Right Join, and Left Join. Inner Join is a type of Join and it is used to intersect two datasets.
Join is a keyword used in many SQL programs. It allows two datasets to be combined in whatever way the user wants. There are four types of Join, namely Inner Join, Outer Join, Right Join, and Left Join. Inner join is the default join keyword. The combined dataset values are stored in one dataset.
Inner Join is a Join keyword and is used in many SQL programs. It is used to combine two datasets by intersecting the datasets. Thus the data values that are common in both datasets are combined into one dataset and stored in that dataset. It is the default join keyword.
Comparison Table
| Parameters of Comparison | Join | Inner Join |
|---|---|---|
| Definition | Join is a keyword used to combine two datasets | Inner join is a type of Join keyword |
| Operation | Different types of join combine datasets differently | Inner join is used to intersect two datasets |
| Default usage | The type of join has to be specified to use a particular operation | Inner join is the default type of join keyword |
| Results | Depending on the join keyword used, different data values are combined in one dataset | Inner join combines the common data values in a single dataset |
| Syntax requirement | The prefix keyword has to be specified for using this keyword | The datasets will be combined even if the “Inner” prefix is not specified |
What is Join?
Join is a keyword used in many SQL programs. SQL programs are used to store large amounts of data, and similar types of data, such as usernames and addresses, are stored in one dataset.
Join is used to combine two datasets. The combined data values are stored in one dataset. This allows for more efficient data storage or in the case when some other operation is to be performed on the combined set of values.
SQL programs offer different types of Join keywords that combine data differently. The default keyword is Join, which directly adds two datasets together and creates a bigger dataset containing all the data values.
Other types of Join keywords are Inner Join, Outer Join, Right Join, and Left Join. These provide different types of combinations for storing the data values.
It is important to specify the prefix of the Join keyword for using the different types of Join functions. If the prefix is not specified, the default join keyword will be operated, and the two datasets will be combined.
The join keyword is commonly used for storing sorted-out data values together, for example, names, account numbers, addresses, and so on, such that similar or common data values are stored in a single repository.
What is Inner Join?
Inner Join is a Join keyword that is provided in SQL and database management programs. It is used to combine two datasets.
Join is the primary keyword and is used to combine two datasets. There are different types of Join keywords, such as Inner join, Outer join, Right join, and Left join, and each keyword performs a different join operation.
Inner join is used to intersect two datasets such that the values that are the same in both datasets are combined. Thus in Inner Join, only the common data values will be combined into one dataset, and the other values will be neglected.
This is slightly different from the default Join keyword, as in the Join keyword, all the data values in the datasets are combined into a single dataset.
Inner Join is used to create a dataset containing all similar data values selectively. It represents the intersection concept of the set theory in database management.
The counterpart to Inner Join is Outer Join, which combines all the other data values which are not at the intersection of the datasets.
Join keywords are mostly used to combine the data values, making it easier to perform operations on the values.
Main Difference Between Join and Inner Join
- Join is a keyword used to combine two datasets together. Inner join is a Join keyword.
- Different types of Join keywords perform different join functions. Inner join is specifically used to intersect two datasets.
- While using the Join keyword, the prefix is important. Inner join is the default join operation.
- Depending on the prefix, different join keywords result in different combinations. Inner join only combines the data values that are commonly present in the datasets.
- If the prefix is not specified, Join will combine the datasets together and return a larger dataset. The intersection of datasets will occur only if the “Inner” keyword is mentioned before Join.
- https://www.researchgate.net/profile/Fawwaz-Alnawajha/publication/292382883_The_Performance_of_Inner_Join_Types_in_SQL/links/56adfa9f08aeaa696f2e8d23/The-Performance-of-Inner-Join-Types-in-SQL.pdf
- https://iopscience.iop.org/article/10.1088/1742-6596/1844/1/012021/meta
Last Updated : 11 June, 2023
I’ve put so much effort writing this blog post to provide value to you. It’ll be very helpful for me, if you consider sharing it on social media or with your friends/family. SHARING IS ♥️
Sandeep Bhandari holds a Bachelor of Engineering in Computers from Thapar University (2006). He has 20 years of experience in the technology field. He has a keen interest in various technical fields, including database systems, computer networks, and programming. You can read more about him on his bio page.
The most crucial part of database management systems is the join operation, where inner joins return the rows with matching values in both tables. The keyword join is very useful, and the different types of joins offer versatility in handling large amounts of data.
Absolutely, understanding the inner joins operation is a critical part of effective database management.
I agree entirely. All these inner join types are essential to store and manage such large amounts of data.
Understanding the inner join in SQL and database management is crucial, and this article does an excellent job of explaining its significance. The comparison table serves as a quick reference guide to differentiate between join and inner join.
The detailed comparison table provides a comprehensive understanding of the difference between Join and Inner Join. It’s very enlightening, and there’s a wealth of valuable information in this article for all levels of database management knowledge.
The precise explanation of join and inner join is exceptionally useful for individuals seeking an in-depth understanding of database management systems. The concise references provided further enhance the content’s credibility.
Indeed, the in-depth breakdown of join operations and the significance of inner joins are quite informative, serving as a valuable resource for professionals in this field.
The article presents a well-detailed description of join and inner join in SQL. It is quite informative and elucidates the difference between the two types of joins. The references provided are useful for further exploration of this topic.
The detailed breakdown of join and inner join, along with elucidating their differences, is a valuable resource for anyone working with database management systems. The concepts are well articulated, providing a clear understanding of inner join operations.
I couldn’t agree more. The explicit details on join and inner join are commendable, providing substantial knowledge for effective database management.
Absolutely, the article delves deep into the technical aspects while maintaining clarity in the explanation of inner joins and their importance.
The detailed explanation and comprehensive comparison between join and inner join are highly informative. It effectively empowers readers to discern the nuances of join operations and understand their applications in database management.
The article provides an exceptional elucidation of join and inner join concepts, emphasizing their critical roles in effective data management. The comparative analysis offers invaluable insights for professionals in this domain.
Absolutely, the comprehensive overview of join and inner join operations is immensely beneficial for individuals looking to gain a profound understanding of database management principles.
The concept of joins, especially inner join, is fundamental in database management systems. The article has effectively conveyed the purpose and utility of various join operations. The references are an added bonus for in-depth research on the topic.