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Comparison of DataNucleus with MySQL server vs DataNucleus with DB4O embedded

Each of the following tables focuses on a specific database operation, where the last table presents average results comparison.

Speed comparison of JPA database persistence operations (normalized score, higher is better)

Transaction Size =>Few EntitiesMany EntitiesAverage Score
 DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
Basic Person Test2.60.0591.41.32.00.69
Element Collection Test1.00.0450.481.00.760.52
Inheritance Test2.50.0511.30.851.90.45
Indexing Test4.00.0802.52.33.31.2
Graph (Binary Tree) Test1.1failed0.99failed1.1failed
Multithreading Test6.2failed2.5failed4.4failed
All Tests2.90.0591.51.42.20.71

DataNucleus with DB4O embedded has failed in 4 tests (see exceptions).

The results above show that in general DataNucleus with MySQL server is much more efficient than DataNucleus with DB4O embedded in persisting JPA entity objects to the database. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.71) to the normalized speed of DataNucleus with MySQL database server (2.2) reveals that in these tests, DataNucleus with MySQL server is 3.1 times faster than DataNucleus with DB4O embedded.

A huge performance gap has been detected when using database indexes with small transaction size. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.080) to the normalized speed of DataNucleus with MySQL database server (4.0) reveals that in that case, DataNucleus with MySQL server is 50.0 times faster than DataNucleus with DB4O embedded.

On the other hand, DataNucleus with MySQL server is slower, for instance, when using JPA element collections with large transaction size. Comparing the normalized speed of DataNucleus with MySQL database server (0.48) to the normalized speed of DataNucleus with DB4O embedded database (1.0) reveals that in that case, DataNucleus with MySQL server is 2.1 times slower than DataNucleus with DB4O embedded.

Speed comparison of JPA database retrieval operations (normalized score, higher is better)

Retrieval Size =>Few EntitiesMany EntitiesAverage Score
 DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
Basic Person Test0.960.00479.31.85.10.90
Element Collection Test0.180.00380.771.50.470.77
Inheritance Test0.550.00358.52.24.51.1
Indexing Test0.820.00439.71.85.30.89
Graph (Binary Tree) Test2.1failed3.5failed2.8failed
Multithreading Test0.27failed7.8failed4.0failed
All Tests0.810.00416.61.83.70.91

DataNucleus with DB4O embedded has failed in 4 tests (see exceptions).

The results above show that in general DataNucleus with MySQL server is much more efficient than DataNucleus with DB4O embedded in retrieving JPA entity objects from the database. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.91) to the normalized speed of DataNucleus with MySQL database server (3.7) reveals that in these tests, DataNucleus with MySQL server is 4.1 times faster than DataNucleus with DB4O embedded.

A huge performance gap has been detected when using simple basic entities with small retrieval size. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.0047) to the normalized speed of DataNucleus with MySQL database server (0.96) reveals that in that case, DataNucleus with MySQL server is 204 times faster than DataNucleus with DB4O embedded.

Speed comparison of JPA database query operations (normalized score, higher is better)

Retrieval Size =>Few EntitiesMany EntitiesAverage Score
 DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
Basic Person Test7.2failed2.2failed4.7failed
Element Collection Test5.8failed0.27failed3.1failed
Inheritance Test2.9failed1.7failed2.3failed
Indexing Test0.0084failed2.5failed1.2failed
Multithreading Testfailedfailedfailedfailedfailedfailed
All Tests4.0failed1.7failed2.8failed

DataNucleus with MySQL server has failed in 2 tests (see exceptions). DataNucleus with DB4O embedded has failed in 10 tests (see exceptions).

Speed comparison of JPA database update operations (normalized score, higher is better)

Transaction Size =>Few EntitiesMany EntitiesAverage Score
 DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
Basic Person Test0.610.0121.10.760.880.39
Element Collection Test0.310.0120.441.10.380.53
Inheritance Test0.510.0111.80.811.10.41
Indexing Test0.680.0112.21.31.50.64
Graph (Binary Tree) Test0.91failed0.47failed0.69failed
Multithreading Test0.64failedfailedfailed0.64failed
All Tests0.610.0121.20.970.880.49

DataNucleus with MySQL server has failed in 1 tests (see exceptions). DataNucleus with DB4O embedded has failed in 4 tests (see exceptions).

The results above show that in general DataNucleus with MySQL server is more efficient than DataNucleus with DB4O embedded in updating JPA entity objects in the database.

A huge performance gap has been detected when using database indexes with small transaction size. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.011) to the normalized speed of DataNucleus with MySQL database server (0.68) reveals that in that case, DataNucleus with MySQL server is 61.8 times faster than DataNucleus with DB4O embedded.

On the other hand, DataNucleus with MySQL server is slower, for instance, when using JPA element collections with large transaction size. Comparing the normalized speed of DataNucleus with MySQL database server (0.44) to the normalized speed of DataNucleus with DB4O embedded database (1.1) reveals that in that case, DataNucleus with MySQL server is 2.5 times slower than DataNucleus with DB4O embedded.

Speed comparison of JPA database removal operations (normalized score, higher is better)

Transaction Size =>Few EntitiesMany EntitiesAverage Score
 DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
Basic Person Test0.700.0111.31.51.00.74
Element Collection Test0.170.0100.401.60.290.80
Inheritance Test0.410.00931.31.10.870.57
Indexing Test1.70.0171.92.11.81.1
Graph (Binary Tree) Test0.49failed0.46failed0.47failed
Multithreading Testfailedfailedfailedfailedfailedfailed
All Tests0.690.0121.11.60.890.79

DataNucleus with MySQL server has failed in 2 tests (see exceptions). DataNucleus with DB4O embedded has failed in 4 tests (see exceptions).

The results above show that in general DataNucleus with MySQL server is slightly more efficient than DataNucleus with DB4O embedded in deleting JPA entity objects from the database.

A huge performance gap has been detected when using database indexes with small transaction size. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.017) to the normalized speed of DataNucleus with MySQL database server (1.7) reveals that in that case, DataNucleus with MySQL server is 100.0 times faster than DataNucleus with DB4O embedded.

On the other hand, DataNucleus with MySQL server is slower, for instance, when using JPA element collections with large transaction size. Comparing the normalized speed of DataNucleus with MySQL database server (0.40) to the normalized speed of DataNucleus with DB4O embedded database (1.6) reveals that in that case, DataNucleus with MySQL server is 4.0 times slower than DataNucleus with DB4O embedded.

Comparison of JPA/Database speed - the averages (normalized score, higher is better)

Transaction/Retrieval SizeFew EntitiesMany EntitiesAverage Score
 DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
DataNucleus
MySQL server
DataNucleus
DB4O embedded
Basic Person Test2.40.0223.11.32.70.68
Element Collection Test1.50.0180.471.30.990.66
Inheritance Test1.40.0192.91.22.10.63
Indexing Test1.40.0283.81.92.60.94
Graph (Binary Tree) Test1.2failed1.4failed1.3failed
Multithreading Test2.4failed5.1failed3.5failed
All Tests1.70.0222.61.42.10.73

The results above show that in general DataNucleus with MySQL server is more efficient than DataNucleus with DB4O embedded in performing JPA database operations. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.73) to the normalized speed of DataNucleus with MySQL database server (2.1) reveals that in these tests, DataNucleus with MySQL server is 2.9 times faster than DataNucleus with DB4O embedded.

A huge performance gap has been detected when using simple basic entities with small transaction/retrieval size. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.022) to the normalized speed of DataNucleus with MySQL database server (2.4) reveals that in that case, DataNucleus with MySQL server is 109 times faster than DataNucleus with DB4O embedded.

On the other hand, DataNucleus with MySQL server is slower, for instance, when using JPA element collections with large transaction/retrieval size. Comparing the normalized speed of DataNucleus with MySQL database server (0.47) to the normalized speed of DataNucleus with DB4O embedded database (1.3) reveals that in that case, DataNucleus with MySQL server is 2.8 times slower than DataNucleus with DB4O embedded.

Other Head to Head DBMS/JPA Comparisons