Advanced Redis Bit Operations: Commands, Underlying Data Structures, Complexity, Storage Calculation, and Use Cases

This article introduces Redis's advanced bitmap (bit) features, aiming to teach readers how to use Redis bit operations and understand their underlying implementation principles.

It covers the following topics:

Redis bit operation command examples

Underlying data structure analysis

Why the algorithms have O(1) time complexity

Storage space required for billions of bits

Suitable application scenarios for Redis bit operations

Redis Bit Operations

Redis provides four bitmap commands: SETBIT , GETBIT , BITCOUNT , and BITOP .

SETBIT

Syntax: SETBIT key offset value

The command writes a binary value (0 or 1) at the specified offset (starting from 0). Writing any value other than 0 or 1 fails.

GETBIT

Syntax: GETBIT key offset

The command retrieves the binary value stored at the given offset.

BITCOUNT

Syntax: BITCOUNT key

This command returns the number of bits set to 1 in the bitmap associated with the key.

BITOP

Syntax: BITOP operation destkey key [key...]

It performs bitwise operations (AND, OR, XOR) on one or more bitmaps and stores the result in destkey .

Underlying Data Structure Analysis

Redis stores strings using SDS (Simple Dynamic String), a binary‑safe structure defined as:

struct sdshdr {
    int len;   // number of used bytes (also the string length)
    int free;  // number of free bytes in the buffer
    char buff[]; // actual byte array containing the string data
}

SDS offers O(1) operations, prevents buffer overflows, reduces memory reallocations when modifying strings, provides binary‑safe APIs, and is compatible with many C string functions.

Bitmaps in Redis are stored as String objects that internally use the SDS structure.

Time Complexity

GETBIT – O(1)

SETBIT – O(1)

BITCOUNT – O(n) (where n is the number of bits, with internal optimizations)

BITOP – O(n) or O(n²) depending on the operation

For SETBIT/GETBIT, the target byte is calculated as offset / 8 and the specific bit within that byte as offset % 8 , resulting in constant‑time computation.

Storage Space Calculation

To store 1 billion bits, the required memory is approximately:

1000000000 ÷ 8 ÷ 1024 ÷ 1024 ≈ 119.21 MB

This fits comfortably within modern Redis instances that often have tens of gigabytes of memory. However, using excessively large offsets for small data sets can waste space.

Application Scenarios

Redis bitmaps are useful in many real‑world projects, such as:

User sign‑in tracking (key = date, offset = user ID)

Active user counting for daily/monthly active users and retention analysis

Online/offline status monitoring and total online user count

Global notification red‑dot indicators in mobile apps