Comparison-of-other-Unique-Identifier.md

Identifier	Creator	Advantages	Disadvantages	Unique Features
ULID	A. Feerasta	- Lexicographically sortable - 128-bit compatibility with UUID - Easily implementable in many languages	- Not natively supported in most databases - Requires additional logic for collision avoidance	- Provides monotonicity within the same millisecond if properly implemented
LexicalUUID	Twitter	- Ensures lexicographical ordering - Ideal for ordered database indexing	- Requires custom implementation - May not be as universally recognized or supported as UUIDs	- Specifically designed to work well with systems that benefit from ordering, such as databases and queues
Snowflake	Twitter	- Highly scalable and distributed - Time-ordered - No central coordination needed	- Complex to implement correctly - Limited to 4096 IDs per millisecond per node	- Combines time, datacenter, machine, and sequence numbers to ensure uniqueness across distributed systems
Flake	Boundary	- Similar to Snowflake, provides time-ordered and distributed IDs - Useful in distributed systems	- Can be complex to manage across different nodes - Requires consistent clock synchronization	- K-ordered IDs are well-suited for systems where time-based ordering is critical
ShardingID	Instagram	- Facilitates sharding in distributed databases - Reduces collision risk across shards	- Implementation complexity - Requires precise control over ID generation	- Helps with the horizontal scaling of databases by ensuring unique identifiers across shards
KSUID	Segment	- K-sortable, allowing for lexicographical sorting - Embedded timestamp - 160-bit, ensuring higher uniqueness	- Larger size than standard UUIDs - Not as widely adopted or supported as traditional UUIDs	- The longer bit length provides additional uniqueness and future-proofing
Elasticflake	P. Pearcy	- Tailored for use with Elasticsearch - Time-ordered and distributed	- Limited to specific use cases like Elasticsearch - Less flexible for general-purpose applications	- Integrates well with Elasticsearch, providing efficient querying and indexing
FlakeID	T. Pawlak	- Simple to implement - Time-ordered and scalable	- Fewer features compared to Snowflake - Potentially limited to certain environments	- Focuses on ease of use and simplicity while retaining core benefits of time-ordering
Sonyflake	Sony	- Optimized for low-latency networks - Time-ordered - Scalable and distributed	- Limited to environments with low network latency - Requires consistent clock synchronization	- Designed for performance in low-latency environments, making it suitable for high-speed transactional systems
orderedUuid	IT. Cabrera	- Ensures time-ordered UUIDs - Useful for ordered databases	- Requires custom implementation - May not be as widely recognized or supported as UUIDs	- Provides the benefits of traditional UUIDs while adding ordering based on creation time
COMBGUID	R. Tallent	- Combines timestamp with randomness - Compatible with standard UUID formats	- More complex to implement - Less intuitive for general use	- Enhances traditional UUIDs by adding time-based components for better sorting
SID	A. Chilton	- Sequential ID generation - Useful in systems where order matters	- Limited flexibility - Not suitable for distributed systems	- Ensures that IDs are generated in a strictly sequential manner, useful for single-system environments
pushID	Google	- Time-ordered - Designed for real-time databases - Short and unique	- Limited to specific environments like Firebase - Smaller address space compared to UUIDs	- Optimized for real-time applications, particularly in Firebase for efficient and unique key generation
XID	O. Poitrey	- Compact size (12 bytes) - Easy to generate - Collision-resistant	- Less entropy than UUIDs - Not widely supported outside of specific use cases	- Smaller size and simpler implementation make it suitable for high-performance and memory-constrained environments
ObjectID	MongoDB	- Incorporates a timestamp, making it time-ordered - Efficient in MongoDB	- Specific to MongoDB - Not universally applicable outside MongoDB	- Designed to work seamlessly with MongoDB, ensuring that document IDs are time-ordered and unique
CUID	E. Elliott	- Collision-resistant - Short and human-readable - Great for distributed systems	- Not as widely recognized as UUIDs - May require additional libraries for implementation	- Focuses on human readability and collision resistance, ideal for systems requiring easily recognizable IDs