Important Data Structures

A comprehensive guide to fundamental and advanced data structures used in software development.

Linear Data Structures

Linked List

Dynamic nodes for efficient insertion and deletion in sequences.

• Nodes connected via pointers (Head → 13 → 36 → 39 → 52 → 65 → Tail)
• O(1) insertion/deletion at known positions
• O(n) search time

Stack

LIFO (Last In, First Out) data structure, supports push and pop operations efficiently.

• Operations: push, pop
• Use cases: undo operations, expression evaluation, backtracking

Queue

FIFO (First In, First Out) linear data structure, supports enqueue and dequeue operations.

• Operations: Enqueue (Front), Dequeue (Rear)
• Use cases: task scheduling, BFS traversal, print spooling

Heap

Priority-based binary tree data structure for efficient operations.

• Min Heap: Parent ≤ children
• Max Heap: Parent ≥ children
• Use cases: priority queues, heap sort

Tree Structures

Tree

Hierarchical structure, efficient for searching and organizing hierarchical relationships.

• Root node with child nodes
• Use cases: file systems, organizational charts

Suffix Tree

String pattern matching with tree-like data structure efficiency.

• Example: “banana$” broken into suffixes
• Use cases: substring search, pattern matching

B-Tree

Balanced search tree for efficient retrieval, commonly used in databases.

• Self-balancing tree structure
• Nodes can have multiple keys (e.g., 20|40 with children 10, 30|33, 50|60)
• Use cases: databases, file systems

R-Tree

Spatial data indexing for rectangles, commonly used in geographic information systems.

• Hierarchical bounding rectangles
• Use cases: GIS, spatial queries

Graph Structures

Graph

Nodes and edges representing relationships, versatile data structure modeling scenarios.

• Vertices (A, B, C, D, E) connected by edges
• Types: directed, undirected, weighted
• Use cases: social networks, routing, dependencies

Hash-Based Structures

Hash Index

Hash function-based data retrieval structure in databases.

• Key → Hash Function → Hash Table → Value
• O(1) average lookup time
• Use cases: database indexing, caches

Inverted Index

Document-to-term mapping for efficient full-text searches in documents.

Document/Term | ID
Cat          | 1, 3, 6
Dog          | 2, 5
Fish         | 4

• Use cases: search engines, text search

Specialized Structures

Skiplist

Probabilistic linked list alternative for efficient searching and insertion.

• Multiple levels of linked lists
• O(log n) search time
• Use cases: Redis sorted sets, concurrent data structures

SSTable (Sorted String Table)

Immutable table for key-value pairs, optimized for write-once, read-many.

• Sorted, immutable segments
• Use cases: LSM-tree storage, Cassandra

LSM Tree (Log-Structured Merge Tree)

Key-value store design, optimizing write-intensive workloads through sorted merging.

• Write to memory → flush to disk → merge sorted runs
• Use cases: LevelDB, RocksDB, Cassandra

Priority Queue

Efficient data structure combining queue and heap properties.

• Elements ordered by priority
• Use cases: task scheduling, Dijkstra’s algorithm

Vertex Buffer

Graphics optimization for efficient storage and rendering of vertex data.

• Use cases: game engines, 3D graphics

Sources

• Arhitectura/data types.jpeg