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Comparison of DataNucleus with PostgreSQL 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
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
Basic Person Test4.10.0592.61.33.30.69
Element Collection Test0.910.0450.381.00.640.52
Inheritance Test3.80.0512.40.853.10.45
Indexing Test6.00.0806.42.36.21.2
Graph (Binary Tree) Test0.91failed0.77failed0.84failed
Multithreading Test18.0failed8.3failed13.1failed
All Tests5.60.0593.51.44.50.71

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

The results above show that in general DataNucleus with PostgreSQL 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 PostgreSQL database server (4.5) reveals that in these tests, DataNucleus with PostgreSQL server is 6.3 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 PostgreSQL database server (6.0) reveals that in that case, DataNucleus with PostgreSQL server is 75.0 times faster than DataNucleus with DB4O embedded.

On the other hand, DataNucleus with PostgreSQL server is slower, for instance, when using JPA element collections with large transaction size. Comparing the normalized speed of DataNucleus with PostgreSQL database server (0.38) to the normalized speed of DataNucleus with DB4O embedded database (1.0) reveals that in that case, DataNucleus with PostgreSQL server is 2.6 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
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
Basic Person Test1.70.00477.61.84.60.90
Element Collection Test0.730.00380.631.50.680.77
Inheritance Test1.50.00359.32.25.41.1
Indexing Test1.50.00439.21.85.30.89
Graph (Binary Tree) Test2.6failed12.3failed7.4failed
Multithreading Test3.4failed10.8failed7.1failed
All Tests1.90.00418.31.85.10.91

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

The results above show that in general DataNucleus with PostgreSQL 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 PostgreSQL database server (5.1) reveals that in these tests, DataNucleus with PostgreSQL server is 5.6 times faster than DataNucleus with DB4O embedded.

A huge performance gap has been detected when using class inheritance in the object model with small retrieval size. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.0035) to the normalized speed of DataNucleus with PostgreSQL database server (1.5) reveals that in that case, DataNucleus with PostgreSQL server is 429 times faster than DataNucleus with DB4O embedded.

On the other hand, DataNucleus with PostgreSQL server is slower, for instance, when using JPA element collections with large retrieval size. Comparing the normalized speed of DataNucleus with PostgreSQL database server (0.63) to the normalized speed of DataNucleus with DB4O embedded database (1.5) reveals that in that case, DataNucleus with PostgreSQL server is 2.4 times slower than DataNucleus with DB4O embedded.

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

Retrieval Size =>Few EntitiesMany EntitiesAverage Score
 DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
Basic Person Test49.1failed4.7failed26.9failed
Element Collection Test39.1failed0.48failed19.8failed
Inheritance Test55.9failed6.6failed31.2failed
Indexing Test0.048failed6.4failed3.2failed
Multithreading Testfailedfailedfailedfailedfailedfailed
All Tests36.0failed4.5failed20.3failed

DataNucleus with PostgreSQL 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
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
Basic Person Test2.10.0120.840.761.50.39
Element Collection Test1.40.0120.641.11.00.53
Inheritance Test2.10.0111.20.811.70.41
Indexing Test2.20.0111.51.31.80.64
Graph (Binary Tree) Test0.65failed0.20failed0.42failed
Multithreading Test0.46failedfailedfailed0.46failed
All Tests1.50.0120.870.971.20.49

DataNucleus with PostgreSQL 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 PostgreSQL server is more efficient than DataNucleus with DB4O embedded in updating JPA entity objects in the database. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.49) to the normalized speed of DataNucleus with PostgreSQL database server (1.2) reveals that in these tests, DataNucleus with PostgreSQL server is 2.4 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 (0.011) to the normalized speed of DataNucleus with PostgreSQL database server (2.2) reveals that in that case, DataNucleus with PostgreSQL server is 200 times faster than DataNucleus with DB4O embedded.

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

Transaction Size =>Few EntitiesMany EntitiesAverage Score
 DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
Basic Person Test3.00.0111.31.52.20.74
Element Collection Test1.00.0100.391.60.690.80
Inheritance Test2.80.00931.31.12.10.57
Indexing Test5.40.0171.92.13.71.1
Graph (Binary Tree) Test0.38failed0.37failed0.37failed
Multithreading Test13.8failedfailedfailed13.8failed
All Tests4.40.0121.11.62.90.79

DataNucleus with PostgreSQL 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 PostgreSQL server is much more efficient than DataNucleus with DB4O embedded in deleting JPA entity objects from the database. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.79) to the normalized speed of DataNucleus with PostgreSQL database server (2.9) reveals that in these tests, DataNucleus with PostgreSQL server is 3.7 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 (0.017) to the normalized speed of DataNucleus with PostgreSQL database server (5.4) reveals that in that case, DataNucleus with PostgreSQL server is 318 times faster than DataNucleus with DB4O embedded.

On the other hand, DataNucleus with PostgreSQL server is slower, for instance, when using JPA element collections with large transaction size. Comparing the normalized speed of DataNucleus with PostgreSQL database server (0.39) to the normalized speed of DataNucleus with DB4O embedded database (1.6) reveals that in that case, DataNucleus with PostgreSQL server is 4.1 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
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
Basic Person Test12.00.0223.41.37.70.68
Element Collection Test8.60.0180.501.34.60.66
Inheritance Test13.20.0194.21.28.70.63
Indexing Test3.00.0285.11.94.00.94
Graph (Binary Tree) Test1.1failed3.4failed2.3failed
Multithreading Test8.9failed9.5failed9.1failed
All Tests8.00.0223.81.46.00.73

The results above show that in general DataNucleus with PostgreSQL server is much 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 PostgreSQL database server (6.0) reveals that in these tests, DataNucleus with PostgreSQL server is 8.2 times faster than DataNucleus with DB4O embedded.

A huge performance gap has been detected when using class inheritance in the object model with small transaction/retrieval size. Comparing the normalized speed of DataNucleus with DB4O embedded database (0.019) to the normalized speed of DataNucleus with PostgreSQL database server (13.2) reveals that in that case, DataNucleus with PostgreSQL server is 695 times faster than DataNucleus with DB4O embedded.

On the other hand, DataNucleus with PostgreSQL server is slower, for instance, when using JPA element collections with large transaction/retrieval size. Comparing the normalized speed of DataNucleus with PostgreSQL database server (0.50) to the normalized speed of DataNucleus with DB4O embedded database (1.3) reveals that in that case, DataNucleus with PostgreSQL server is 2.6 times slower than DataNucleus with DB4O embedded.

Other Head to Head DBMS/JPA Comparisons