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Comparison of DataNucleus with DB4O embedded vs DataNucleus with PostgreSQL server

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
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
Basic Person Test0.0594.11.32.60.693.3
Element Collection Test0.0450.911.00.380.520.64
Inheritance Test0.0513.80.852.40.453.1
Indexing Test0.0806.02.36.41.26.2
Graph (Binary Tree) Testfailed0.91failed0.77failed0.84
Multithreading Testfailed18.0failed8.3failed13.1
All Tests0.0595.61.43.50.714.5

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
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
Basic Person Test0.00471.71.87.60.904.6
Element Collection Test0.00380.731.50.630.770.68
Inheritance Test0.00351.52.29.31.15.4
Indexing Test0.00431.51.89.20.895.3
Graph (Binary Tree) Testfailed2.6failed12.3failed7.4
Multithreading Testfailed3.4failed10.8failed7.1
All Tests0.00411.91.88.30.915.1

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
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
Basic Person Testfailed49.1failed4.7failed26.9
Element Collection Testfailed39.1failed0.48failed19.8
Inheritance Testfailed55.9failed6.6failed31.2
Indexing Testfailed0.048failed6.4failed3.2
Multithreading Testfailedfailedfailedfailedfailedfailed
All Testsfailed36.0failed4.5failed20.3

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

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

Transaction Size =>Few EntitiesMany EntitiesAverage Score
 DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
Basic Person Test0.0122.10.760.840.391.5
Element Collection Test0.0121.41.10.640.531.0
Inheritance Test0.0112.10.811.20.411.7
Indexing Test0.0112.21.31.50.641.8
Graph (Binary Tree) Testfailed0.65failed0.20failed0.42
Multithreading Testfailed0.46failedfailedfailed0.46
All Tests0.0121.50.970.870.491.2

DataNucleus with DB4O embedded has failed in 4 tests (see exceptions). DataNucleus with PostgreSQL server has failed in 1 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
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
Basic Person Test0.0113.01.51.30.742.2
Element Collection Test0.0101.01.60.390.800.69
Inheritance Test0.00932.81.11.30.572.1
Indexing Test0.0175.42.11.91.13.7
Graph (Binary Tree) Testfailed0.38failed0.37failed0.37
Multithreading Testfailed13.8failedfailedfailed13.8
All Tests0.0124.41.61.10.792.9

DataNucleus with DB4O embedded has failed in 4 tests (see exceptions). DataNucleus with PostgreSQL server has failed in 1 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
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
DataNucleus
DB4O embedded
DataNucleus
PostgreSQL server
Basic Person Test0.02212.01.33.40.687.7
Element Collection Test0.0188.61.30.500.664.6
Inheritance Test0.01913.21.24.20.638.7
Indexing Test0.0283.01.95.10.944.0
Graph (Binary Tree) Testfailed1.1failed3.4failed2.3
Multithreading Testfailed8.9failed9.5failed9.1
All Tests0.0228.01.43.80.736.0

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