Red Black Tree vs AVL Tree

In this post we will compare Red Black Tree and AVL Tree.

** Red Black Tree**:

** Properties**:

- Self-Balancing is provided by painting each node with one two colors(Red or Black).
- When Tree is modified, new tree is subsequently rearranged and repainted.
- It requires 1 bit of color information for each node in tree.

** Constraints maintained by Red Black Tree**:

- Root is always black.
- All NULL leaves are black, both children of red node are black.
- Every simple path from a given node to any of its descendant leaves contains the same number of black

nodes. - Path form root to farthest leaf is no more than twice as long as path from root to nearest leaf.

**AVL(Adelson-Velskii and Landis) Tree**

** Properties**:

- Height difference of left and right subtree of node should be less than 2.
- Re-balancing is done when heights of two child subtrees of a node differ by more than one.
- Faster retrievals as strictly balanced.

*Difference*:

- AVL trees provide
**faster lookups**than Red Black Trees because they are more strictly balanced. - Red Black Trees provide
**faster insertion and removal**operations than AVL trees as fewer rotations are done due to relatively relaxed balancing. - AVL trees store
**balance factors or heights**with each node, thus requires storage for an integer per node whereas Red Black Tree requires only 1 bit of information per node. - Red Black Trees are used in most of the language libraries like
**map**,**multimap**,**multiset**in C++ whereas AVL trees are used in**databases**where faster retrievals are required.

Attention reader! Don’t stop learning now. Get hold of all the important DSA concepts with the **DSA Self Paced Course** at a student-friendly price and become industry ready.