A data structure said to be linear if its elements are connected in linear or in sequence. Example of linear data structures are queue and stack. Non linear data structures are those data structure in which data items are not in sequence. For example, binary tree.

An Abstract Data Type (ADT) is a description on how we view the data and allow user to abstract away from implementation details. Advantages of ADT are modularity, which it is much easier to debug small routines than large routines and it also easier several people to work on a program simultaneously. Next, ADT also have encapsulation as it can access by well-defined interface only.

Disadvantages of ADT are insertion and deletion process is slow and it has redundant memory space as it will be difficult to estimate the size of array.

1) Allows easier processing of data.
2) Allows information stored on disk very efficiently .
3) These are necessary for designing an efficient algorithm.
4) We can access data anytime and anywhere. 

1) It is applicable only for advanced users.
2)Only can be solved by experts when any issues occurs.
3) Slow access in case of some data types 

There are two types of data structure: primitive data structures and non-primitive data structure.

Pro and cons of different data structures:-

Pros:
-> Access to an array element is fast since we can compute its location quickly.
Cons:
-> If we want to insert or delete an element, we have to shift subsequent elements which slows our computation down.

Linked Lists –
 Pros:
-> Inserting and deleting data does not require us to move/shift subsequent data elements.

->Linked lists require more memory.

-> Not easily corrupted.

-> Creating too many objects on the stack will increase the chances of stack overflow.

Queue -
 Pros:

-> Not easily corrupted 

Cons:
-> Random access not possible

Tree -
 Pros:
-> Searching is faster (with some ordering e.g., BST). We can search for a given key in moderate time (quicker than Linked List and slower than arrays)

Cons:
-> High overhead

Heap -
 Pros:

-> It can offer the maximum memory an OS can provide

Cons:
-> You must make sure to free the memory when you are done

Graph -
 Pros:
-> Finding the path in efficient way
Cons:
-> High overhead

--> Every data structure is used to organize the large amount of data
 --> Every data structure follows a particular principle
--> The operations in a data structure should not violate the basic principle of that data structure.

Based on the organizing method of a data structure, data structures are divided into two types.

If a data structure is organizing the data in sequential order, then that data structure is called as Linear Data Structure. For example:

- Arrays, List (Linked List), Stack, Queue

If a data structure is organizing the data in random order, then that data structure is called as Non-Linear Data Structure. For example:

- Tree, Graph, Dictionaries, Heaps, Tries

anything that can store data can be called as a data structure, hence Integer, Float, Boolean, Char etc, all are data structures. They are known as Primitive Data Structures.

Then we also have some complex Data Structures, which are used to store large and connected data. Some example of Abstract Data Structure are :

All these data structures allow us to perform different operations on data. We select these data structures based on which type of operation is required.