What is Base64 Encoding?

Understanding Base64 encoding, how it works, and why it's essential for web development.

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What is Base64?

Base64 is a binary-to-text encoding scheme that represents binary data in an ASCII string format. It's called "Base64" because it uses 64 different characters to represent data: A-Z, a-z, 0-9, +, and /.

Why Do We Need Base64?

Many systems were designed to handle text, not binary data. Email protocols, HTML, CSS, and URLs all have limitations on what characters they can safely transmit. Base64 solves this by converting binary data into a safe text format.

Common Use Cases

  • Data URLs: Embedding images directly in HTML/CSS
  • Email attachments: MIME encoding for binary files
  • API authentication: Basic Auth headers use Base64
  • Storing binary in JSON/XML: These formats only support text

How Base64 Works

  • Take the binary input
  • Split into 6-bit chunks (2^6 = 64 possible values)
  • Map each chunk to one of 64 characters
  • Pad with "=" if the input isn't divisible by 3 bytes

Size Consideration

Base64 encoded data is approximately 33% larger than the original. This is because 3 bytes of binary become 4 bytes of Base64 text.

// Example: Encoding a string
const encoded = btoa("Hello, World!");
// Result: "SGVsbG8sIFdvcmxkIQ=="

const decoded = atob("SGVsbG8sIFdvcmxkIQ==");
// Result: "Hello, World!"

Frequently Asked Questions

Common questions about this topic

Base64 uses 64 characters: uppercase letters A-Z (26), lowercase letters a-z (26), digits 0-9 (10), plus sign (+), and forward slash (/). The equals sign (=) is used for padding. Base64URL variant uses minus (-) and underscore (_) instead of + and /.

Base64 converts every 3 bytes (24 bits) of binary data into 4 characters (6 bits each). This 3:4 ratio means the output is always 4/3 ≈ 1.33 times the input size, plus padding. This overhead is the cost of safely encoding binary as text.

Avoid Base64 for: large files (33% overhead adds up), security purposes (it's encoding, not encryption), data that stays in binary systems, and performance-critical applications where the encoding/decoding overhead matters.