Have you heard something about file organization in DBMS? Do you know what it is? If not, then don't worry. Board Infinity helps you to clear your doubts.

In this article, we will discuss file organization in DBMS. In DBMS, there are many different ways to organize files. We learn about sequential, heap, cluster, B+ tree, and ISAM, to name a few, along with each method's benefits and drawbacks. Let us understand what file organization in DBMS is.

File Organization: What is It?

File organization describes the logical connections between the different records that make up a file, especially when it comes to the methods for identifying and accessing any particular record. Simply put, file organization is the practice of storing files in a specific order. File structure describes the layout of logical control records, label and data blocks, and any other such block. Let us discuss the purpose of file organization in DBMS.


The purposes of file organization are mentioned below:

  • It has a perfect selection of records, allowing for the quickest selection of records.
  • The insert, delete, or update operations on the records should be simple and quick.
  • No amount of inserting, updating, or deleting can result in duplicate records.
  • Records should be stored effectively to incur the least storage expense.

Types of File Organization

Let us discuss the types of file organization in DBMS.

There are several ways to organize files. Based on access or selection, these specific strategies have benefits and drawbacks. In terms of file organization, the programmer selects the approach that best suits his needs.

The following are the types of file organization in DBMS:

  • Sequential File Organization
  • Hash File Organization
  • Heap File Organization
  • Clustered File Organization
  • B+ Tree File Organization

Let us understand them one by one.

Sequential File Organization

As the name suggests, this method simply stores the records in files in sequential order, one after another in a series like a sequence of books on a bookshelf. To access these files, we must search through the entire sequence until we reach our desired file in O(n), provided there is no order in the files, such as they are unsorted; otherwise, we can use binary search to access in O(logn).

Depending on the ordering structure of the records, there are two ways to arrange them sequentially.

Pile File Method

Records are stored in this method sequentially, one after another, and they are inserted at the end of the file in the same order that we insert them in the table using the SQL query, so it is just an O(1) space complexity operation since the order of the records does not matter.

Sorted Method

As the name implies, the file in this method must always be kept in sorted order. In this approach, the file is sorted using a primary key or another reference after each delete, insert, and update operation.


  • A fast and effective approach for handling massive amounts of data.
  • Plain design
  • Files can be easily saved on magnetic tapes, which is a less expensive storage method.


  • Time is wasted because we have to move sequentially and take our time instead of jumping right to the record that is needed.
  • The sorted file method wastes time and space sorting records, making it inefficient.

Hash File Organization

Hashing is used in hash file organization to create the addresses of the memory blocks where actual records are mapped. In essence, a hashing function creates the address of those data blocks using the primary key as input, and the memory locations created by these hash functions are referred to as data buckets or data blocks. Let us understand its advantages and disadvantages.


  • Hash file organization in DBMS uses a hashing function that quickly returns the bucket address of any record, making it a very quick and effective method.
  • It is used in large databases for online banking, e-commerce, and ticketing because it works quickly and effectively.
  • Due to each record's independence and the ability to access multiple records concurrently, hash file organization in DBMS can handle multiple transactions simultaneously.


  • There is only one column that can be searched, the one that is used to hash bucket addresses. All other columns cannot be searched.
  • Because the hash is a randomly generated bucket address and lacks order, memory is not utilized effectively in this method.

Heap File Organization

Data blocks are used in heap file organization. Records are inserted using this method into the data blocks at the file's end. This method doesn't call for any sorting or ordering. The new record is stored in a new block if a data block is full. In this case, the other block does not necessarily have to be the next data block; it can be any block in the memory. The task of managing and storing the new records falls to the DBMS. Let us understand its advantages and disadvantages.


  • Fetching and retrieving records is quicker for small databases than sequential record access.
  • This file organization method works best when a significant amount of data must be loaded into the database.


  • Unused memory blocks are the problem.
  • Larger databases find it ineffective.

Clustered File Organization

In a clustered file organization, multiple records or tables are combined into a single file based on the clustered key or hash clusters; these files contain multiple tables in the same memory block, and they are all combined using a single clustered key/hash key to a single table. There are two types of clustered file organization, indexed and hash cluster. Let us understand its advantages and disadvantages.


  • When there is a join operation for the tables, the DBMS uses the cluster file organization.
  • This approach is effective when there is a 1:M relationship.


  • The less often connected tables and the tables with one-to-one relationships are inefficient for clustered file arrangement in DBMS.
  • Large databases cannot efficiently use DBMS clustered file organization.

B+ Tree File Organization

As its name implies, B+ Tree uses a tree-like structure to store records in a file. According to the key indexing principle, the primary key is used to sort the records. A produced index value is associated with the record for each primary key. An index of a record is a record's file address.

With the exception of having more children than just two, B+ Tree and binary search tree are extremely similar. The leaf nodes are where all the information is kept, while the intermediate nodes serve as pointers to those nodes. A sorted sequential linked list represents the data in leaf nodes at all times. Let us understand its advantages and disadvantages.


  • It's quicker and simpler to traverse a tree.
  • All records are stored only in leaf nodes and are arranged in a sequential linked list makes searching simple.
  • The size of a B+ tree is not constrained. As the size of the data changes, it might expand or contract.


The only disadvantage of using this method is for static tables. It is ineffective.


In this article, we have discussed file organization in DBMS. The computer's physical memory contains files that, at the lowest level, represent all the tables we construct using SQL. Records are mapped using spanned or unspanned mapping within the disc blocks that make up the memory.

A database can be made more effective for insert, delete, and update operations by using file organization, which groups record using different storage techniques like hashing, sequential, B+ trees, etc. The frequency of accessing the appropriate file organization style is selected to ensure the most effective database, depending on the size of the database and the kind of records.