Besides the quadruple disk space used, which may be largely negligible after additional data is added, they appear to me to be the same. What I am essentially trying to discover is difference in efficiency between the two approaches. Let’s start with the pair: UUIDTOBIN/BINTOUUID. These will ease the work with UUIDs and will provide a solution around the issues mentioned above. Do not expect the first 16 hex bits to contain time and. Solution: With these problems in mind, we added three new functions: UUIDTOBIN, BINTOUUID, ISUUID. The use case for this type of set up would be the traditional primary key for inter-table relationships, with unique identifier used for inter-system relationships. Many people store UUID as char (36) and use as row identity value (PRIMARY KEY) because it is unique across every table, every database and every server and. c) Globally unique id (within 100+ years) in 8-4-4-4-12 format. Whereas many people stress over the advantages of either, what are the disadvantages cancelled out by using both data types? UUID is by definition, 'collision-less', that is the. The problem of duplicate entries in the database is not that uuid is not unique, it is that a new uuid is not being generated for a different node revision id, and that should not go in. I was initially sceptical towards using UUIDs as primary keys, and indeed I still am, however I see potential here to create a flexible database that can use both. The problem of uniqueness is about generating different uuids, and that part is working perfectly afaik. The test and results are shown below, but if you just want the summary, it indicates that INT AUTOINCREMENT and BINARY(16) RANDOM have identical performance on data ranges up to 200,000 (the database was pre-populated prior to tests). ![]() It was when I reached the final one BINARY(16) that I started to compare performance with basic auto-increment integer. The formats I used changed as I became less naive from: 1 In mysql database I have user table and I need to add userkey column where values will be computed as uuid (). I've been using UUIDs in my systems for a while now for a variety of reasons ranging from logging to delayed correlation.
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