diff --git a/search/ternary_search.ts b/search/ternary_search.ts
new file mode 100644
index 00000000..c6f96778
--- /dev/null
+++ b/search/ternary_search.ts
@@ -0,0 +1,62 @@
+/**
+ * @function ternarySearch
+ * @description Ternary search is a divide-and-conquer search algorithm similar to binary search.
+ * It divides the search space into three parts instead of two. It's useful for searching in sorted arrays,
+ * especially for searching peaks in mountains or similar structures. It can also be used as an alternative to binary search.
+ * @Complexity_Analysis
+ * Space complexity - O(log₃ n)  (recursion depth)
+ * Time complexity
+ *      Best case   -   O(1)
+ *                      When the element is at one of the dividing points
+ *      Worst case  -   O(log₃ n)
+ *                      When we need to go through the entire search tree
+ *      Average case -  O(log₃ n)
+ *
+ * @param {number[]} arr - The sorted input array
+ * @param {number} target - The target value to search
+ * @return {number} - The index of the target if found, otherwise -1
+ * @see [Ternary Search](https://en.wikipedia.org/wiki/Ternary_search)
+ * @example ternarySearch([1, 2, 3, 4, 5, 6, 7, 8, 9], 5) = 4
+ */
+
+export function ternarySearch(arr: number[], target: number): number {
+  return ternarySearchHelper(arr, target, 0, arr.length - 1);
+}
+
+function ternarySearchHelper(
+  arr: number[],
+  target: number,
+  left: number,
+  right: number,
+): number {
+  if (left > right) {
+    return -1;
+  }
+
+  // Divide the array into 3 parts
+  const mid1 = Math.floor(left + (right - left) / 3);
+  const mid2 = Math.floor(right - (right - left) / 3);
+
+  // Check if target is at mid1
+  if (arr[mid1] === target) {
+    return mid1;
+  }
+
+  // Check if target is at mid2
+  if (arr[mid2] === target) {
+    return mid2;
+  }
+
+  // If target is less than mid1, search in left third
+  if (target < arr[mid1]) {
+    return ternarySearchHelper(arr, target, left, mid1 - 1);
+  }
+
+  // If target is greater than mid2, search in right third
+  if (target > arr[mid2]) {
+    return ternarySearchHelper(arr, target, mid2 + 1, right);
+  }
+
+  // If target is between mid1 and mid2, search in middle third
+  return ternarySearchHelper(arr, target, mid1 + 1, mid2 - 1);
+}
diff --git a/search/test/ternary_search.test.ts b/search/test/ternary_search.test.ts
new file mode 100644
index 00000000..82ec2f69
--- /dev/null
+++ b/search/test/ternary_search.test.ts
@@ -0,0 +1,36 @@
+import { ternarySearch } from '../ternary_search';
+
+describe('Ternary Search', () => {
+  test('should find the target element', () => {
+    expect(ternarySearch([1, 2, 3, 4, 5, 6, 7, 8, 9], 5)).toBe(4);
+  });
+
+  test('should return -1 when target is not found', () => {
+    expect(ternarySearch([1, 2, 3, 4, 5, 6, 7, 8, 9], 10)).toBe(-1);
+  });
+
+  test('should find the first element', () => {
+    expect(ternarySearch([1, 2, 3, 4, 5], 1)).toBe(0);
+  });
+
+  test('should find the last element', () => {
+    expect(ternarySearch([1, 2, 3, 4, 5], 5)).toBe(4);
+  });
+
+  test('should handle single element array', () => {
+    expect(ternarySearch([5], 5)).toBe(0);
+  });
+
+  test('should return -1 for single element array when target not found', () => {
+    expect(ternarySearch([5], 3)).toBe(-1);
+  });
+
+  test('should handle empty array', () => {
+    expect(ternarySearch([], 5)).toBe(-1);
+  });
+
+  test('should find element in array with duplicates', () => {
+    const result = ternarySearch([1, 2, 2, 2, 3, 4, 5], 2);
+    expect([1, 2, 3]).toContain(result);
+  });
+});
diff --git a/sorts/radix_sort.ts b/sorts/radix_sort.ts
new file mode 100644
index 00000000..382c87c5
--- /dev/null
+++ b/sorts/radix_sort.ts
@@ -0,0 +1,63 @@
+/**
+ * @function radixSort
+ * @description Radix sort is a non-comparative integer sorting algorithm that sorts numbers by processing digits.
+ * It works by sorting elements digit by digit, starting from the least significant digit to the most significant digit.
+ * This algorithm is efficient for sorting large numbers of integers with a fixed number of digits.
+ * @Complexity_Analysis
+ * Space complexity - O(n + k) where k is the range of input
+ * Time complexity
+ *      Best case   -   O(n * d)
+ *                      where d is the number of digits
+ *      Worst case  -   O(n * d)
+ *                      where d is the number of digits
+ *      Average case -  O(n * d)
+ *                      where d is the number of digits
+ *
+ * @param {number[]} arr - The input array
+ * @return {number[]} - The sorted array
+ * @see [Radix Sort](https://en.wikipedia.org/wiki/Radix_sort)
+ * @example radixSort([170, 45, 75, 90, 2, 802, 24, 2, 66]) = [2, 2, 24, 45, 66, 75, 90, 170, 802]
+ */
+
+export function radixSort(arr: number[]): number[] {
+  if (arr.length === 0) return arr;
+
+  const max = Math.max(...arr);
+  let exp = 1;
+
+  while (max / exp > 0) {
+    countingSortByDigit(arr, exp);
+    exp *= 10;
+  }
+
+  return arr;
+}
+
+function countingSortByDigit(arr: number[], exp: number): void {
+  const n = arr.length;
+  const output: number[] = new Array(n);
+  const count: number[] = new Array(10).fill(0);
+
+  // Count occurrences of each digit
+  for (let i = 0; i < n; i++) {
+    const digit = Math.floor((arr[i] / exp) % 10);
+    count[digit]++;
+  }
+
+  // Change count[i] so that count[i] contains actual position
+  for (let i = 1; i < 10; i++) {
+    count[i] += count[i - 1];
+  }
+
+  // Build the output array
+  for (let i = n - 1; i >= 0; i--) {
+    const digit = Math.floor((arr[i] / exp) % 10);
+    output[count[digit] - 1] = arr[i];
+    count[digit]--;
+  }
+
+  // Copy the output array to arr
+  for (let i = 0; i < n; i++) {
+    arr[i] = output[i];
+  }
+}
diff --git a/sorts/test/radix_sort.test.ts b/sorts/test/radix_sort.test.ts
new file mode 100644
index 00000000..a2f5830c
--- /dev/null
+++ b/sorts/test/radix_sort.test.ts
@@ -0,0 +1,29 @@
+import { radixSort } from '../radix_sort';
+
+describe('Radix Sort', () => {
+  test('should sort an unsorted array', () => {
+    expect(radixSort([170, 45, 75, 90, 2, 802, 24, 2, 66])).toEqual([
+      2, 2, 24, 45, 66, 75, 90, 170, 802,
+    ]);
+  });
+
+  test('should sort a single element array', () => {
+    expect(radixSort([5])).toEqual([5]);
+  });
+
+  test('should sort an already sorted array', () => {
+    expect(radixSort([1, 2, 3, 4, 5])).toEqual([1, 2, 3, 4, 5]);
+  });
+
+  test('should sort a reverse sorted array', () => {
+    expect(radixSort([5, 4, 3, 2, 1])).toEqual([1, 2, 3, 4, 5]);
+  });
+
+  test('should handle empty array', () => {
+    expect(radixSort([])).toEqual([]);
+  });
+
+  test('should sort array with duplicate elements', () => {
+    expect(radixSort([3, 3, 1, 1, 2])).toEqual([1, 1, 2, 3, 3]);
+  });
+});