Indexing in Database

Aditya kumar
Last Updated: May 13, 2022


Indexing improves database performance by reducing the number of disk accesses necessary when a query is run. It's a data structure strategy for finding and accessing data in a database rapidly.


An Index-

  • As input, it accepts a search key.
  • Returns a group of matching records quickly.


The indexing has several characteristics:

  • Access Types: This relates to the access method, such as value-based search, range access, and so on.
  • Access Time: It refers to the amount of time it takes to locate a specific data element or combination of data elements.
  • Insertion Time. Refers to the time it takes to find and insert new data into the right place.
  • Deletion Time: Time it takes to locate an item, delete it, and update the index structure.
  • Space Overhead: It refers to the extra space that the index necessitates.


Types of Indexing



Source: Types of Indexing


The indexing properties of a database specify its indexing. There are two primary types of indexing methods:

  • Primary Indexing
  • Secondary Indexing

Primary Index

A primary index is a two-field, ordered file with a defined length. The first field is the same as the primary key, while the second field points to the data block in question. There is always a one-to-one relationship between the entries in the index table in the primary index.

The primary indexing in a database management system is also divided into two types:

  • Dense Index
  • Sparse Index

Dense Index

For each search key value in the database, a record is created in a dense index. This allows you to search more quickly, but it requires more storage space for index information. Method records in this Indexing contain the search key value and point to the real record on the disk.

Source: Dense Index


Sparse Index

It's an index record that only appears for a subset of the file's values. Sparse indexes assist you in resolving DBMS dense indexing challenges. This indexing approach keeps the same data block address in a series of index columns, and when data is needed, the block address is retrieved.


Sparse Index, on the other hand, only keeps index entries for a subset of search-key values. It takes up less space and has a smaller maintenance overhead for insertions and deletions, but it is slower to locate records than a dense index.


Source: Sparse Index


Secondary Index

In a database management system, a secondary index can be constructed by a field that has a unique value for each record and should be a candidate key. A non-clustering index is another name for it.

To reduce the size of the first-level mapping, this two-level database indexing strategy is applied. Because of this, a wide range of values is chosen for the first level, and the mapping size is always kept minimal.

Clustering Index

The records themselves, not references, are stored in a clustered index. Non-primary key columns are sometimes used to build indexes, and they may not be unique for each record. In this case, you can aggregate two or more columns to generate unique values and create a clustered index. This also aids in the faster identification of the record.

What is a Multilevel Index, and how does it work?

When a primary index is too large to fit in memory, multilevel indexing is used. You can reduce the amount of disk access by shortening any record and keeping it on a disc as a sequential file, then creating a sparse base on that file using this indexing strategy.

Source: Multilevel Indexing


B-Tree Index

In relational databases, the B-tree index is the most extensively used data structure for tree-based indexing. It's a multilevel tree-based indexing strategy in DBMS that uses balanced binary search trees. The B tree's leaf nodes represent actual data references.

Furthermore, a link list connects all leaf nodes, allowing a B tree to enable random and sequential access.

Source: B-Tree


  • Between 2 and 4 values are required for lead nodes.
  • Every path from the root to the leaf is roughly the same length.
  • Apart from the root node, non-leaf nodes have between 3 and 5 offspring nodes.
  • There are between n/2 and n children for every node that isn't a root or a leaf.

Advantages of Indexing

  • It allows you to reduce the total number of I/O operations required to retrieve that data by eliminating the necessity to access a database entry through an index structure.
  • Users may search and retrieve info more quickly.
  • You can save tablespace by indexing because you don't need to connect to a row in a table. After all, the ROWID isn't stored in the index. As a result, you will be able to save table space.
  • The value of the main key classifies the data in the lead nodes, so you can't sort it.

Disadvantages of Indexing

  • A primary key on the table with a unique value is required to accomplish the indexing database management system.
  • On the Indexed data, you can't conduct any additional indexes in the Database.
  • Partitioning an index-organized table is not permitted.
  • SQL indexing reduces the speed of INSERT, DELETE, and UPDATE queries.

Frequently Asked Question

1. What is the difference between Primary and Secondary indexing?

For the difference, we are going to consider the following characteristics of them, which are given below:

  • Definition

A primary index is a collection of fields that includes the primary key and is guaranteed to be duplicate-free. A secondary index, on the other hand, is not a primary index and may contain duplicates.

  • Order

The primary index requires that the rows in data blocks be arranged according to the index key, whereas the secondary index has no bearing on how the rows are grouped in data blocks.

  • Number of Indexes

Furthermore, there is only one primary index, whereas subsidiary indexes can be several.

  • Duplicates

There are no duplicates in the primary index. However, duplicates in the secondary index are possible.

2. What is the difference between Clustered and non clustered indexes?

Clustered Index
Cluster indexes are indexes that rank data rows in a table based on their key values. There is only one clustered index per table in the database.
The order in which data is stored in a table that can only be sorted in one direction is defined by a clustered index. 

Non-Clustered Index
A non-clustered index keeps the data in one place and the indices in another. The index provides references to the data's location. As an index in a non-clustered index is kept in several places, a single table might have many non-clustered indexes.

3. What kind of Data structure is an index?

The indexes are usually stored using the B-Tree data structure. This is due to B-Trees' high efficiency in terms of time. In other words, logarithmic time is used to traverse, search, insert, delete, and update B-trees. Furthermore, B-Tree data is always sorted and saved. As a result, searching and entering data takes a predictable amount of time.

Key takeaway

In this article, we learned about Indexing in databases and their various types. We got to know the significant classification of indexes in three parts, However, i.e., primary index, secondary index, and clustering index. In DBMS, a secondary index is an indexing strategy in which the search key specifies a different order than the file's sequential order. A clustering index is defined as an order data file. When a primary index cannot fit in memory, multilevel indexing is used.

You can also learn about the implementation of indexing and SQLite by clicking here. Learn indexing and SQLite.

If you want to master DBMS, then you can check our guided path on DBMS.

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