Abstract: A semantic layer (universe), which is created on a source database (DB), is migrated to a target DB. The migration includes pre-migration steps, actual migration and post-migration steps. The pre-migration steps prepare the target DB for the actual migration by configuring the target DB and determining the differences between the source DB and the target DB. During the actual migration, data, tables and views are migrated to the target DB conforming to the target database structure, functions and configuration. A new universe is created on the target database and all consumers of the source universe such as created reports are changed to refer to the new universe.

Abstract: In one aspect, a Universe designed and built in a database is used for modeling data in an in-memory database. The Universe is loaded in a front-end development application to display a universe schema contained in the Universe. The logic built in the front-end development application enables parsing the universe schema, to determine patterns matching in-memory views such as attribute views and analytic views. The determined patterns are generated as attribute views and analytic views, and displayed for user selection. Selected attribute views and analytic views are stored in the in-memory database.

Abstract: A semantic layer (universe), which is created on a source database (DB), is migrated to a target DB. The migration includes pre-migration steps, actual migration and post-migration steps. The pre-migration steps prepare the target DB for the actual migration by configuring the target DB and determining the differences between the source DB and the target DB. During the actual migration, data, tables and views are migrated to the target DB conforming to the target database structure, functions and configuration. A new universe is created on the target database and all consumers of the source universe such as created reports are changed to refer to the new universe.

Abstract: In one aspect, a Universe designed and built in a database is used for modeling data in an in-memory database. The Universe is loaded in a front-end development application to display a universe schema contained in the Universe. The logic built in the front-end development application enables parsing the universe schema, to determine patterns matching in-memory views such as attribute views and analytic views. The determined patterns are generated as attribute views and analytic views, and displayed for user selection. Selected attribute views and analytic views are stored in the in-memory database.

Abstract: Various embodiments of systems and methods of translating SQL queries are described herein. A structured query language (SQL) query of a first database is split into tokens and traversed from a first token. When a keyword token is encountered, a current parser is created to store a table name and a column name associated with the encountered keyword token. When an open parenthesis is encountered, a token immediately preceding the open parenthesis is stored as a function name in the current parser. The table names, column names, and function names of a plurality of parsers are consolidated. One or more of the table names, the column names, and the function names are replaced with corresponding names that are compatible with SQL-syntax of a second database. A result comprising the consolidated table names, the consolidated column names, the consolidated function names, and replaced names is generated.