Difference Between Join and Inner Join (With Table)

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 the customer information of a company. Database management systems also feature different operations and functions that can be performed on the data that is stored.

Join vs Inner Join

The main 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 ways 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 type of 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 the datasets are combined into one dataset and stored in that dataset. It is the default join keyword.

Comparison Table Between Join and Inner Join

Parameters of ComparisonJoinInner Join
Definition Join is a keyword used to combine two datasetsInner join is a type of Join keyword
OperationDifferent types of join combine datasets differentlyInner join is used to intersect two datasets
Default usage The type of join has to be specified to use a particular operationInner join is the default type of join keyword
Results Depending on the join keyword used, different data values are combined in one datasetInner join combines the common data values in a single dataset
Syntax requirementThe prefix keyword has to be specified for using this keywordThe 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.

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 type 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 generally used to combine two datasets. There are different types of Join keywords, such as Inner join, Outer join, Right join, 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 selectively create a dataset that contains all the similar data values. 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 so that it becomes easier to perform operations on the values.

Main Difference Between Join and Inner Join

  1. Join is a keyword used to combine two datasets together. Inner join is a type of Join keyword
  2. Different types of Join keywords perform different join functions. Inner join is specifically used to intersect two datasets.
  3. While using Join keyword the prefix is important. Inner join is the default join operation.
  4. 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.
  5. If the prefix is not specified, Join will combine the datasets together and return a larger dataset. Intersection of datasets will occur only if the “Inner” keyword is mentioned before Join.

Conclusion

The data obtained from users or customers are stored in database management systems and SQL programs. In such programs, many times similar data are stored which later have to be sorted according to their similarity.

Although Join and Inner Join do not sort the data, they help in combining datasets such that all the data is stored in a single dataset.

Join is the keyword used for combining datasets and it majorly has four types, Inner Join, Outer Join, Right Join, and Left Join. The four Join keywords help in combining the datasets in a particular order.

Inner Join is used to combine the datasets that have similar data values. Thus it represents the intersection concept of set theory in programming.

References

  1. 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
  2. https://iopscience.iop.org/article/10.1088/1742-6596/1844/1/012021/meta
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