🔧 Top 15 Data Structures Every Developer Should Know

1️⃣ Array
– Fixed-size, index-based structure.
– Fast read, slow insert/delete.

2️⃣ Linked List
– Elements connected via pointers.
– Efficient insert/delete, slow access.

3️⃣ Stack (LIFO)
– Push/pop only from one end.
– Used in undo features, recursion.

4️⃣ Queue (FIFO)
– Enqueue at rear, dequeue from front.
– Used in scheduling, messaging systems.

5️⃣ Hash Table / HashMap
– Key-value storage with fast access.
– Used in caching, databases.

6️⃣ Set
– Stores unique elements.
– Good for membership checks.

7️⃣ Tree
– Hierarchical structure.
– Used in file systems, parsers.

8️⃣ Binary Search Tree (BST)
– Tree with ordered nodes.
– Efficient search, insert, delete.

9️⃣ Heap
– Complete binary tree (min/max).
– Used in priority queues, heapsort.

🔟 Graph
– Nodes and edges.
– Used in maps, networks, social media.

1️⃣1️⃣ Trie
– Prefix tree for strings.
– Used in autocomplete, dictionary.

1️⃣2️⃣ Deque (Double-ended queue)
– Add/remove from both ends.
– Combination of stack and queue.

1️⃣3️⃣ Matrix
– 2D array for mathematical operations.
– Used in games, ML, image processing.

1️⃣4️⃣ Union-Find (Disjoint Set)
– Track a set of elements split into groups.
– Used in Kruskal's algorithm, social networks.

1️⃣5️⃣ Bloom Filter
– Probabilistic data structure.
– Checks for membership with space efficiency.

💡 Pro Tip: Master operations, use cases & time complexity for interviews.

❤️ React for more!