Abstract: Methods and systems are disclosed improving run-time performance of a database. A development database comprising code is accessed. Data statistics are generated based on testing the code against performance metrics of a second database, the data statistics based on the performance metrics of how the development database would perform as the second database. The data statistics and at least one suggestion to implement into the code of the development database to improve a performance of the development database is displayed.

Abstract: Methods and systems are disclosed improving run-time performance of a database. A development database comprising code is accessed, at a computer system. Code of the development database is tested against a data set. Data statistics are generated, at the computer system, based on performance metrics of how the development database would perform using the data set. The data statistics and at least one suggestion to implement into code of the development database to improve performance of the development database are displayed at the computer system.

Abstract: Methods and systems are disclosed improving run-time performance of a database. A non-production database is accessed, at a computer system, during a design phase of the non-production database, wherein the non-production database will be converted to a production database after the design phase. Data statistics are generated, at the computer system, based on performance metrics of how the non-production database would perform as the production database. The data statistics are displayed, at the computer system, to a developer of the non-production database during the design phase. At least one suggestion is offered to the developer, at the computer system, to implement into the SQL of the non-production database to improve a performance of the non-production database.

Abstract: Methods and systems are disclosed improving run-time performance of a database. A non-production database is accessed, at a computer system, during a design phase of the non-production database. Code of the non-production database is tested against a production database. Data statistics are generated, at the computer system, based on performance metrics of how the non-production database would perform as the production database. The data statistics and at least one suggestion to implement into code of the non-production database to improve performance of the non-production database are displayed at the computer system.

Abstract: Methods and systems are disclosed improving run-time performance of a database. A non-production database is accessed, at a computer system, during a design phase4 of the non-production database, wherein the non-production database will be converted to a production database after the design phase. Data statistics are generated, at the computer system, based on performance metrics of how the non-production database would perform as the production database. The data statistics are displayed, at the computer system, to a developer of the non-production database during the design phase. At least one suggestion is offered to the developer, at the computer system, to implement into the SQL of the non-production database to improve a performance of the non-production database.

Abstract: Methods and systems are disclosed improving run-time performance of a database. A non-production database is accessed, at a computer system, during a design phase4 of the non-production database, wherein the non-production database will be converted to a production database after the design phase. Data statistics are generated, at the computer system, based on performance metrics of how the non-production database would perform as the production database. The data statistics are displayed, at the computer system, to a developer of the non-production database during the design phase. At least one suggestion is offered to the developer, at the computer system, to implement into the SQL of the non-production database to improve a performance of the non-production database.

Abstract: A virtual database is attached to a server database management system (“DBMS”) such that the DBMS believes it needs to recover the database to a last known point of consistency. In order to perform this recovery, the DBMS requests the transaction log file entries to be read from what it believes is the database's transaction log file. However, the requests are intercepted and translated into requests to read the transaction log portion of the backup file. The DBMS then uses the transaction log records to bring the database to a point of transactional consistency, unaware that the log records are actually being sourced from the backup file. All changes made to the data during the recovery phase and subsequent execution of any TSQL statements are routed into a cache file. Accordingly, a “virtual” database is created and used by the server DBMS engine as if it were a real database.

Abstract: Methods and systems are disclosed improving run-time performance of a database. A non-production database is accessed, at a computer system, during a design phase4 of the non-production database, wherein the non-production database will be converted to a production database after the design phase. Data statistics are generated, at the computer system, based on performance metrics of how the non-production database would perform as the production database. The data statistics are displayed, at the computer system, to a developer of the non-production database during the design phase. At least one suggestion is offered to the developer, at the computer system, to implement into the SQL of the non-production database to improve a performance of the non-production database.

Abstract: A virtual database is attached to a server database management system (“DBMS”) such that the DBMS believes it needs to recover the database to a last known point of consistency. In order to perform this recovery, the DBMS requests the transaction log file entries to be read from what it believes is the database's transaction log file. However, the requests are intercepted and translated (unbeknownst to the DBMS) instead into requests to read the transaction log portion of the backup file. The DBMS then uses the transaction log records to bring the database to a point of transactional consistency, unaware that the log records are actually being sourced from the transaction log portion of the backup file. All changes made to the data during the recovery phase and later during the execution of any TSQL statements which insert, update, or delete data are routed into a cache file. Accordingly, a “virtual” database is created and used by the server DBMS engine as if it were a real database.