Vs (Linear & Binary & Tree & Hash search)
Description
| Linear search | Binary search | Tree search | Hash search | |
|---|---|---|---|---|
| Search element | \(O(n)\) | \(O(\log n)\) | \(O(\log n)\) | \(O(1)\) |
| Insert element | \(O(1)\) | \(O(n)\) | \(O(\log n)\) | \(O(1)\) |
| Delete element | \(O(n)\) | \(O(n)\) | \(O(\log n)\) | \(O(1)\) |
| Extra space | \(O(1)\) | \(O(1)\) | \(O(n)\) | \(O(n)\) |
| Data preprocessing | / | Sorting \(O(n \log n)\) | Building tree \(O(n \log n)\) | Building hash table \(O(n)\) |
| Data orderliness | Unordered | Ordered | Ordered | Unordered |
- Linear search: Is ideal for small or frequently updated (volatile) data.
- Binary search: Works well for large and sorted data.
- Hash search: Is suitable for data that requires high query efficiency and does not need range queries.
- Tree search: Is best suited for large dynamic data that require maintaining order and need to support range queries.