Generic semantic layer for in-memory database reporting

1. A system for combining online transactional processing and online analytical processing in an in-memory database, comprising:

the in-memory database that is configured to execute a method comprising:

retrieving two or more tables from an online transaction processing system;

identifying related tables among the two or more tables;

determining, by a hardware processor, relationships between the related tables, wherein determining the relationships comprises analyzing metadata of the related tables;

determining a measure based on the relationships; and

outputting the measure.

2. The system of claim 1 , wherein the tables of the online transaction processing system are replicated in the in-memory database.

3. The system of claim 1 , wherein the method further comprises:

determining a business object among the tables that identifies a main table among the tables which provides information for linking the related tables.

4. The system of claim 3 , wherein the business object is a representation of an intelligible business or non-business entity, such as an account, an order, employee, an invoice or a financial report.

5. The system of claim 1 , wherein the determining of the measure based on the relationships comprises:

identifying the measure in the related tables based on data types of table columns and based on semantic words used in the tables; and

calculating the measure using the relationships of the related tables.

6. The system of claim 1 , wherein the outputting of the measure comprises:

associating the measure with a subset of columns and/or rows from the related tables and outputting the measure with the subset of columns and/or rows.

7. A method for combining online transactional processing and online analytical processing in an in-memory database, comprising:

retrieving two or more tables from an online transaction processing system;

identifying related tables among the two or more tables;

determining, by a hardware processor, relationships between the related tables, wherein determining the relationships comprises analyzing metadata of the related tables;

determining a measure based on the relationships; and

outputting the measure.

8. The method of claim 7 , wherein the tables of the online transaction processing system are replicated in the in-memory database.

9. The method of claim 7 , wherein the method further comprises:

determining a business object among the tables that identifies a main table among the tables which provides information for linking the related tables.

10. The method of claim 9 , wherein the business object is a representation of an intelligible business or non-business entity, such as an account, an order, employee, an invoice or a financial report.

11. The method of claim 7 , wherein the determining of the measure based on the relationships comprises:

identifying the measure in the related tables based on data types of table columns and based on semantic words used in the tables; and

calculating the measure using the relationships of the related tables.

12. The method of claim 7 , wherein the outputting of the measure comprises:

associating the measure with a subset of columns and/or rows from the related tables and outputting the measure with the subset of columns and/or rows.

13. A non-transitory computer-readable medium having computer-executable instructions stored thereon that, when executed by a processor, cause the processor to perform a method for combining online transactional processing and online analytical processing in an in-memory database, comprising:

retrieving two or more tables from an online transaction processing;

identifying related tables among the two or more tables;

determining relationships between the related tables, wherein determining the relationships comprises analyzing metadata of the related tables;

determining a measure based on the relationships; and

outputting the measure.

14. The non-transitory computer-readable medium of claim 13 , wherein the tables of the online transaction processing are replicated in the in-memory database.

15. The non-transitory computer-readable medium of claim 13 , wherein the method further comprises:

determining a business object among the tables that identifies a main table among the tables which provides information for linking the related tables.

16. The non-transitory computer-readable medium of claim 15 , wherein the business object is a representation of an intelligible business or non-business entity, such as an account, an order, employee, an invoice or a financial report.

17. The non-transitory computer-readable medium of claim 13 , wherein the determining of the measure based on the relationships comprises:

identifying the measure in the related tables based on data types of table columns and based on semantic words used in the tables; and

calculating the measure using the relationships of the related tables.

18. The non-transitory computer-readable medium of claim 13 , wherein the outputting of the measure comprises:

associating the measure with a subset of columns and/or rows from the related tables and outputting the measure with the subset of columns and/or rows.

19. A system for combining online transactional processing and online analytical processing in an in-memory database, comprising:

the in-memory database that is configured to execute a method comprising:

retrieving two or more tables from an online transaction processing system, wherein the tables of the online transaction processing system are replicated in the in-memory database;

identifying related tables among the two or more tables, comprising:

determining a business object among the tables that identifies a main table among the tables which provides information for linking the related tables;

analyzing metadata of the tables to identify the related tables;

determining, by a hardware processor, relationships between the related tables by analyzing the metadata of the tables;

determining a measure based on the relationships; and

associating the measure with a subset of columns and/or rows from the related tables and outputting the measure with the subset of columns and/or rows.