Comparison of DataNucleus with PostgreSQL server vs DataNucleus with H2 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 Entities | Many Entities | Average Score | |||
---|---|---|---|---|---|---|
  | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded |
Basic Person Test | 4.1 | 19.2 | 2.6 | 8.0 | 3.3 | 13.6 |
Element Collection Test | 0.91 | 6.6 | 0.38 | 2.8 | 0.64 | 4.7 |
Inheritance Test | 3.8 | 15.6 | 2.4 | 4.4 | 3.1 | 10.0 |
Indexing Test | 6.0 | 24.4 | 6.4 | 11.8 | 6.2 | 18.1 |
Graph (Binary Tree) Test | 0.91 | 9.2 | 0.77 | 6.2 | 0.84 | 7.7 |
Multithreading Test | 18.0 | 34.9 | 8.3 | 7.1 | 13.1 | 21.0 |
All Tests | 5.6 | 18.3 | 3.5 | 6.7 | 4.5 | 12.5 |
The results above show that in general DataNucleus with H2 embedded is more efficient than DataNucleus with PostgreSQL server in persisting JPA entity objects to the database. Comparing the normalized speed of DataNucleus with PostgreSQL database server (4.5) to the normalized speed of DataNucleus with H2 embedded database (12.5) reveals that in these tests, DataNucleus with H2 embedded is 2.8 times faster than DataNucleus with PostgreSQL server.
A huge performance gap has been detected when using graphs of objects with small transaction size. Comparing the normalized speed of DataNucleus with PostgreSQL database server (0.91) to the normalized speed of DataNucleus with H2 embedded database (9.2) reveals that in that case, DataNucleus with H2 embedded is 10.1 times faster than DataNucleus with PostgreSQL server.
Speed comparison of JPA database retrieval operations (normalized score, higher is better)
Retrieval Size => | Few Entities | Many Entities | Average Score | |||
---|---|---|---|---|---|---|
  | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded |
Basic Person Test | 1.7 | 13.2 | 7.6 | 13.5 | 4.6 | 13.3 |
Element Collection Test | 0.73 | 6.4 | 0.63 | 8.9 | 0.68 | 7.7 |
Inheritance Test | 1.5 | 12.2 | 9.3 | 12.7 | 5.4 | 12.4 |
Indexing Test | 1.5 | 8.1 | 9.2 | 16.5 | 5.3 | 12.3 |
Graph (Binary Tree) Test | 2.6 | 10.6 | 12.3 | 20.9 | 7.4 | 15.8 |
Multithreading Test | 3.4 | 13.3 | 10.8 | 9.9 | 7.1 | 11.6 |
All Tests | 1.9 | 10.6 | 8.3 | 13.7 | 5.1 | 12.2 |
The results above show that in general DataNucleus with H2 embedded is more efficient than DataNucleus with PostgreSQL server in retrieving JPA entity objects from the database. Comparing the normalized speed of DataNucleus with PostgreSQL database server (5.1) to the normalized speed of DataNucleus with H2 embedded database (12.2) reveals that in these tests, DataNucleus with H2 embedded is 2.4 times faster than DataNucleus with PostgreSQL server.
A huge performance gap has been detected 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 H2 embedded database (8.9) reveals that in that case, DataNucleus with H2 embedded is 14.1 times faster than DataNucleus with PostgreSQL server.
Speed comparison of JPA database query operations (normalized score, higher is better)
Retrieval Size => | Few Entities | Many Entities | Average Score | |||
---|---|---|---|---|---|---|
  | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded |
Basic Person Test | 49.1 | 4.7 | 4.7 | 1.4 | 26.9 | 3.1 |
Element Collection Test | 39.1 | 5.0 | 0.48 | 2.4 | 19.8 | 3.7 |
Inheritance Test | 55.9 | 3.8 | 6.6 | 1.6 | 31.2 | 2.7 |
Indexing Test | 0.048 | 0.0041 | 6.4 | 1.8 | 3.2 | 0.91 |
Multithreading Test | failed | 1.2 | failed | 0.79 | failed | 1.0 |
All Tests | 36.0 | 3.0 | 4.5 | 1.6 | 20.3 | 2.3 |
DataNucleus with PostgreSQL server has failed in 2 tests (see exceptions).
The results above show that in general DataNucleus with PostgreSQL server is much more efficient than DataNucleus with H2 embedded in executing the tested JPA queries. Comparing the normalized speed of DataNucleus with H2 embedded database (2.3) to the normalized speed of DataNucleus with PostgreSQL database server (20.3) reveals that in these tests, DataNucleus with PostgreSQL server is 8.8 times faster than DataNucleus with H2 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 H2 embedded database (3.8) to the normalized speed of DataNucleus with PostgreSQL database server (55.9) reveals that in that case, DataNucleus with PostgreSQL server is 14.7 times faster than DataNucleus with H2 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 (0.48) to the normalized speed of DataNucleus with H2 embedded database (2.4) reveals that in that case, DataNucleus with PostgreSQL server is 5.0 times slower than DataNucleus with H2 embedded.
Speed comparison of JPA database update operations (normalized score, higher is better)
Transaction Size => | Few Entities | Many Entities | Average Score | |||
---|---|---|---|---|---|---|
  | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded |
Basic Person Test | 2.1 | 10.0 | 0.84 | 3.9 | 1.5 | 6.9 |
Element Collection Test | 1.4 | 7.6 | 0.64 | 3.9 | 1.0 | 5.8 |
Inheritance Test | 2.1 | 9.4 | 1.2 | 4.4 | 1.7 | 6.9 |
Indexing Test | 2.2 | 10.6 | 1.5 | 5.9 | 1.8 | 8.2 |
Graph (Binary Tree) Test | 0.65 | 5.9 | 0.20 | 3.7 | 0.42 | 4.8 |
Multithreading Test | 0.46 | failed | failed | failed | 0.46 | failed |
All Tests | 1.5 | 8.7 | 0.87 | 4.4 | 1.2 | 6.5 |
DataNucleus with PostgreSQL server has failed in 1 tests (see exceptions). DataNucleus with H2 embedded has failed in 2 tests (see exceptions).
The results above show that in general DataNucleus with H2 embedded is much more efficient than DataNucleus with PostgreSQL server in updating JPA entity objects in the database. Comparing the normalized speed of DataNucleus with PostgreSQL database server (1.2) to the normalized speed of DataNucleus with H2 embedded database (6.5) reveals that in these tests, DataNucleus with H2 embedded is 5.4 times faster than DataNucleus with PostgreSQL server.
A huge performance gap has been detected when using graphs of objects with large transaction size. Comparing the normalized speed of DataNucleus with PostgreSQL database server (0.20) to the normalized speed of DataNucleus with H2 embedded database (3.7) reveals that in that case, DataNucleus with H2 embedded is 18.5 times faster than DataNucleus with PostgreSQL server.
Speed comparison of JPA database removal operations (normalized score, higher is better)
Transaction Size => | Few Entities | Many Entities | Average Score | |||
---|---|---|---|---|---|---|
  | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded |
Basic Person Test | 3.0 | 4.2 | 1.3 | 1.3 | 2.2 | 2.8 |
Element Collection Test | 1.0 | 4.9 | 0.39 | 1.6 | 0.69 | 3.2 |
Inheritance Test | 2.8 | 4.0 | 1.3 | 1.3 | 2.1 | 2.7 |
Indexing Test | 5.4 | 7.5 | 1.9 | 1.9 | 3.7 | 4.7 |
Graph (Binary Tree) Test | 0.38 | 5.6 | 0.37 | 4.1 | 0.37 | 4.8 |
Multithreading Test | 13.8 | failed | failed | failed | 13.8 | failed |
All Tests | 4.4 | 5.2 | 1.1 | 2.0 | 2.9 | 3.6 |
DataNucleus with PostgreSQL server has failed in 1 tests (see exceptions). DataNucleus with H2 embedded has failed in 2 tests (see exceptions).
The results above show that in general DataNucleus with H2 embedded is slightly more efficient than DataNucleus with PostgreSQL server in deleting JPA entity objects from the database.
A huge performance gap has been detected when using graphs of objects with small transaction size. Comparing the normalized speed of DataNucleus with PostgreSQL database server (0.38) to the normalized speed of DataNucleus with H2 embedded database (5.6) reveals that in that case, DataNucleus with H2 embedded is 14.7 times faster than DataNucleus with PostgreSQL server.
Comparison of JPA/Database speed - the averages (normalized score, higher is better)
Transaction/Retrieval Size | Few Entities | Many Entities | Average Score | |||
---|---|---|---|---|---|---|
  | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded | DataNucleus PostgreSQL server | DataNucleus H2 embedded |
Basic Person Test | 12.0 | 10.3 | 3.4 | 5.6 | 7.7 | 7.9 |
Element Collection Test | 8.6 | 6.1 | 0.50 | 3.9 | 4.6 | 5.0 |
Inheritance Test | 13.2 | 9.0 | 4.2 | 4.9 | 8.7 | 6.9 |
Indexing Test | 3.0 | 10.1 | 5.1 | 7.6 | 4.0 | 8.9 |
Graph (Binary Tree) Test | 1.1 | 7.8 | 3.4 | 8.7 | 2.3 | 8.3 |
Multithreading Test | 8.9 | 16.5 | 9.5 | 5.9 | 9.1 | 11.2 |
All Tests | 8.0 | 9.6 | 3.8 | 6.0 | 6.0 | 7.8 |
The results above show that in general DataNucleus with H2 embedded is more efficient than DataNucleus with PostgreSQL server in performing JPA database operations.
A large performance gap has been detected 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 H2 embedded database (3.9) reveals that in that case, DataNucleus with H2 embedded is 7.8 times faster than DataNucleus with PostgreSQL server.
Other Head to Head DBMS/JPA Comparisons
DataNucleus with PostgreSQL server against:
- Oracle Database 11g
- IBM DB2 10
- Microsoft SQL Server 2008
- DataNucleus with Derby embedded
- DataNucleus with H2 embedded
- DataNucleus with HSQLDB embedded
- DataNucleus with DB4O embedded
- DataNucleus with Derby server
- DataNucleus with H2 server
- DataNucleus with MySQL server
- EclipseLink with Derby embedded
- EclipseLink with H2 embedded
- EclipseLink with HSQLDB embedded
- EclipseLink with SQLite embedded
- EclipseLink with Derby server
- EclipseLink with H2 server
- EclipseLink with MySQL server
- EclipseLink with PostgreSQL server
- Hibernate with Derby embedded
- Hibernate with H2 embedded
- Hibernate with HSQLDB embedded
- Hibernate with SQLite embedded
- Hibernate with Derby server
- Hibernate with H2 server
- Hibernate with MySQL server
- Hibernate with PostgreSQL server
- OpenJPA with Derby embedded
- OpenJPA with H2 embedded
- OpenJPA with HSQLDB embedded
- OpenJPA with Derby server
- OpenJPA with H2 server
- OpenJPA with MySQL server
- OpenJPA with PostgreSQL server
- ObjectDB embedded
- ObjectDB server
DataNucleus with H2 embedded against:
- Oracle Database 11g
- IBM DB2 10
- Microsoft SQL Server 2008
- DataNucleus with Derby embedded
- DataNucleus with HSQLDB embedded
- DataNucleus with DB4O embedded
- DataNucleus with Derby server
- DataNucleus with H2 server
- DataNucleus with MySQL server
- DataNucleus with PostgreSQL server
- EclipseLink with Derby embedded
- EclipseLink with H2 embedded
- EclipseLink with HSQLDB embedded
- EclipseLink with SQLite embedded
- EclipseLink with Derby server
- EclipseLink with H2 server
- EclipseLink with MySQL server
- EclipseLink with PostgreSQL server
- Hibernate with Derby embedded
- Hibernate with H2 embedded
- Hibernate with HSQLDB embedded
- Hibernate with SQLite embedded
- Hibernate with Derby server
- Hibernate with H2 server
- Hibernate with MySQL server
- Hibernate with PostgreSQL server
- OpenJPA with Derby embedded
- OpenJPA with H2 embedded
- OpenJPA with HSQLDB embedded
- OpenJPA with Derby server
- OpenJPA with H2 server
- OpenJPA with MySQL server
- OpenJPA with PostgreSQL server
- ObjectDB embedded
- ObjectDB server