How to set up WUID with Redis for distributed ID generation?

Initialize a Redis client and use the LoadH28FromRedis function, as shown in the README example. Ensure Redis is running and accessible to all instances to guarantee uniqueness across your system.

WUID vs Snowflake: which is better for microservices?

WUID is faster and simpler if you have a shared data source like Redis, while Snowflake offers built-in time ordering and no external dependency but is slower. Choose WUID for raw speed and Snowflake for self-contained time-based IDs.

Does WUID support time-based IDs like ULID?

No, WUID generates sequential 64-bit integers based on a data source, not timestamps. If you need time-ordered IDs for sorting or event tracking, consider alternatives like ULID or XID instead.

How to handle renewal failures in WUID?

Pass a logger to NewWUID and monitor for 'renew failed' warnings, as advised in the README. WUID will retry automatically, but persistent failures may require manual intervention to ensure data source connectivity.

Can I use WUID without an external database?

Yes, via the callback option for custom logic, but you must implement uniqueness guarantees yourself, which adds development overhead and complexity compared to built-in data sources.

What are the security implications of WUID obfuscation?

Obfuscation is optional and helps prevent ID guessing attacks by scrambling numbers, but it's not enabled by default. Enable it with WithObfuscation for enhanced security in sensitive applications.

wuid — Fast Globally Unique Number Generator

What is wuid?

WUID is a universal unique identifier generator designed for high-performance applications. It generates sequential 64-bit integers, with the high 28 bits loaded from a data source like Redis, MySQL, or MongoDB, ensuring uniqueness across distributed instances. It solves the need for extremely fast, distributed, and sequential ID generation without the overhead of traditional UUIDs.

Target Audience

Developers building distributed systems, microservices, or high-throughput applications that require fast, unique, and sequential identifier generation, such as those using Go for backend services.

Value Proposition

Developers choose WUID for its extreme performance—capable of generating 100 million IDs per second per instance—and its flexibility in supporting multiple data sources for distributed uniqueness, offering a lightweight, lock-free alternative to slower UUID implementations.

An extremely fast globally unique number generator.

Use Cases

Best For

High-throughput distributed systems needing millions of unique IDs per second
Microservices architectures requiring sequential, globally unique identifiers across instances
Applications using Redis, MySQL, or MongoDB as a coordination point for ID generation
Scenarios where performance-critical ID generation must avoid locks or bottlenecks
Systems that benefit from obfuscated or partitioned IDs for security or organization
Go-based projects seeking a faster alternative to UUIDv1/v4 or Snowflake-like ID generators

Not Ideal For

Applications requiring human-readable or string-based IDs for web API compatibility
Systems that need ID generation without external dependencies, such as embedded or offline environments
Projects where time-ordered IDs with embedded timestamps are essential, like for event sourcing
Teams using non-Go languages without a port, as support is limited primarily to Go and Swift

Pros & Cons

Pros

Extreme Performance

Benchmarks show WUID generates IDs at 7.661 ns/op, far faster than UUIDs (43-310 ns/op) and alternatives like Snowflake (2092 ns/op), enabling 100M IDs/sec per instance.

Flexible Data Sources

Supports Redis, MySQL, MongoDB, and custom callbacks for loading high bits, ensuring distributed uniqueness without locking, as demonstrated in the usage examples.

Thread-Safe Design

Built to be lock-free and thread-safe, allowing concurrent ID generation without bottlenecks, which is critical for high-throughput applications.

Automatic Renewal

Automatically refreshes high 28 bits when low bits are nearly exhausted, reducing manual oversight and ensuring continuous operation.

Cons

External Dependency Overhead

Requires setting up and maintaining an external data source (e.g., Redis, MySQL) for uniqueness, adding operational complexity and potential failure points, as highlighted by the need to monitor 'renew failed' warnings.

Setup Complexity

Initial configuration involves database-specific setups, like creating MySQL tables or Redis keys, which can be error-prone and time-consuming compared to drop-in solutions.

Limited Metadata Support

Generates plain 64-bit integers without embedded timestamps or machine identifiers, making it less suitable for debugging or auditing compared to IDs like ULID or Snowflake.

What is wuid?

Target Audience

Developers building distributed systems, microservices, or high-throughput applications that require fast, unique, and sequential identifier generation, such as those using Go for backend services.

Value Proposition

Use Cases

Best For

High-throughput distributed systems needing millions of unique IDs per second
Microservices architectures requiring sequential, globally unique identifiers across instances
Applications using Redis, MySQL, or MongoDB as a coordination point for ID generation
Scenarios where performance-critical ID generation must avoid locks or bottlenecks
Systems that benefit from obfuscated or partitioned IDs for security or organization
Go-based projects seeking a faster alternative to UUIDv1/v4 or Snowflake-like ID generators

Not Ideal For

Applications requiring human-readable or string-based IDs for web API compatibility
Systems that need ID generation without external dependencies, such as embedded or offline environments
Projects where time-ordered IDs with embedded timestamps are essential, like for event sourcing
Teams using non-Go languages without a port, as support is limited primarily to Go and Swift

Pros & Cons

Pros

Extreme Performance

Benchmarks show WUID generates IDs at 7.661 ns/op, far faster than UUIDs (43-310 ns/op) and alternatives like Snowflake (2092 ns/op), enabling 100M IDs/sec per instance.

Flexible Data Sources

Supports Redis, MySQL, MongoDB, and custom callbacks for loading high bits, ensuring distributed uniqueness without locking, as demonstrated in the usage examples.

Thread-Safe Design

Built to be lock-free and thread-safe, allowing concurrent ID generation without bottlenecks, which is critical for high-throughput applications.

Automatic Renewal

Automatically refreshes high 28 bits when low bits are nearly exhausted, reducing manual oversight and ensuring continuous operation.

Cons

External Dependency Overhead

Setup Complexity

Initial configuration involves database-specific setups, like creating MySQL tables or Redis keys, which can be error-prone and time-consuming compared to drop-in solutions.

Limited Metadata Support

Generates plain 64-bit integers without embedded timestamps or machine identifiers, making it less suitable for debugging or auditing compared to IDs like ULID or Snowflake.

wuid

What is wuid?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?

wuid

What is wuid?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?