https://github.com/ragin-lundf/hibernate-uuid-vs-int-pk
Simple Benchmark for UUID7 vs INT PK insert
https://github.com/ragin-lundf/hibernate-uuid-vs-int-pk
Last synced: 28 days ago
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Simple Benchmark for UUID7 vs INT PK insert
- Host: GitHub
- URL: https://github.com/ragin-lundf/hibernate-uuid-vs-int-pk
- Owner: Ragin-LundF
- Created: 2025-09-05T18:22:18.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2025-09-05T20:24:52.000Z (about 1 month ago)
- Last Synced: 2025-09-05T21:25:11.356Z (about 1 month ago)
- Language: Kotlin
- Size: 62.5 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Benchmark UUID7 Primary Key vs BIGINT Primary Key Performance in PostgreSQL
Just a very simple repository to benchmark the performance of UUID7 primary keys vs BIGINT primary keys in PostgreSQL.
You can start the application and use the shell to execute the following commands:
Help:
```shell
help
```
Test with BIGINT:
```shell
run-int-insert
```
Test with UUIDv4 (default Hibernate implementation for `@UuidGenerator`, which uses random UUIDs):
```shell
run-uuid-insert
```
Test with UUIDv7 (just create a UUID7 at object creation time):
```shell
run-uuid7insert
```
Test with UUIDv7 (with UUIDv7 auto generation with own annotation for sequence):
```shell
run-uuid7auto-insert
```
## Results
The test was executed on a Mac Pro M1 Max.
```
shell:>run-int-insert
Created 1000000 INT entries in 380.661541ms ms
Inserted 1000000 entries with INT in 12619 ms
Total time INT Insert: 13004 ms
shell:>run-uuid-insert
Created 1000000 UUID entries in 59.922125ms ms
Inserted 1000000 entries with UUID in 14371 ms
Total time UUID Insert: 14432 ms
shell:>run-uuid7insert
Created 1000000 UUID7 entries in 496.876833ms ms
Inserted 1000000 entries with UUID7 in 129546 ms
Total time UUID7 Insert: 130043 ms
shell:>run-uuid7auto-insert
Created 1000000 UUID7 Auto entries in 63.345166ms ms
Inserted 1000000 entries with UUID7 Auto in 13038 ms
Total time UUID7 Auto Insert: 13101 ms
```
## Table sizes
After inserting 1,000,000 entries, the table sizes were as follows:
| Table Name | Index Name | Total Size | Index Size | Table Size | Number of Rows |
|------------------|-----------------------|------------|------------|------------|----------------|
| int_table | int_table_pkey | 87 MB | 21 MB | 65 MB | 1000000 |
| uuid7_auto_table | uuid7_auto_table_pkey | 88 MB | 30 MB | 57 MB | 1000000 |
| uuid7_table | uuid7_table_pkey | 88 MB | 30 MB | 57 MB | 1000000 |
| uuid_table | uuid_table_pkey | 95 MB | 38 MB | 57 MB | 1000000 |
Statement:
```postgresql
SELECT i.relname "Table Name",indexrelname "Index Name",
pg_size_pretty(pg_total_relation_size(relid)) As "Total Size",
pg_size_pretty(pg_indexes_size(relid)) as "Total Size of all Indexes",
pg_size_pretty(pg_relation_size(relid)) as "Table Size",
reltuples::bigint "Estimated table row count"
FROM pg_stat_all_indexes i JOIN pg_class c ON i.relid=c.oid
WHERE i.relname in('int_table', 'uuid7_auto_table', 'uuid7_table', 'uuid_table');
```
## Additional Infos
You can configure the size of the datasets in the `application.yaml` file:
```yaml
dbinsert:
data:
size: 100
log:
batch:
enabled: true
```
- `dbinsert.data.size` - defines the size of the dataset to insert
- `dbinsert.log.batch.enabled` - if true, the application will log the inserts to see if batch was used