Abstract: Data transformation workflows may be generated to transform data objects. A source data schema for a data object and a target data format or target data schema for a data object may be identified. A comparison of the source data schema and the target data format or schema may be made to determine what transformations can be performed to transform the data object into the target data format or schema. Code to execute the transformation operations may then be generated. The code may be stored for subsequent modification or execution.

Abstract: Data transformation workflows may be generated to transform data objects. A source data schema for a data object and a target data format or target data schema for a data object may be identified. A comparison of the source data schema and the target data format or schema may be made to determine what transformations can be performed to transform the data object into the target data format or schema. Code to execute the transformation operations may then be generated. The code may be stored for subsequent modification or execution.

Abstract: Data transformation workflows may be generated to transform data objects. A source data schema for a data object and a target data format or target data schema for a data object may be identified. A comparison of the source data schema and the target data format or schema may be made to determine what transformations can be performed to transform the data object into the target data format or schema. Code to execute the transformation operations may then be generated. The code may be stored for subsequent modification or execution.

Abstract: Version controlled Extract, Transform, Load (ETL) code may be hosted for developing or executing the ETL job in an ETL system. A version of ETL code may be obtained from version controlled code store and maintained in a data store. Development or execution clients may submit access requests for the version of ETL code which may be serviced from the version stored in the data store. Updates to the version of the ETL code may be eventually committed to the version controlled code store. The latest version of ETL code may also be obtained from the version controlled code store when providing the ETL code in response to a request to retrieve the ETL code.

Abstract: A first column of a first database table may be transferred to a second table in a combined truncate and append operation in a transaction that may be atomic and reversible. References data for the first column may be removed from the first table and added to the second table. The combined operation may be reversed by removing, from the second table, references to blocks of data added to the second table prior to commencing the combined operation. A second column corresponding on a row-by-row basis to the first column may be added to the second table, where the data is indicative of visibility of data in the first column to other transactions on the second table.

Abstract: A balanced distribution of sort order values may be implemented for a multi-column sort order of a database table. Columns of the database table to be included in the multi-column sort order may be identified. Some columns containing string data values may be converted to equally-sized integer data values. The data values of columns may be evaluated to determine buckets representing the ranges of data values within the columns for depth-balanced histograms of the columns. Multi-column sort order values may be generated for individual entries in the database table according to bucket values assigned to the buckets that include the columns values of the individual entries. The entries of the database table may then be stored according to a sorted ordering of multi-column sort order values for the entries.

Abstract: Data transformation workflows may be generated to transform data objects. A source data schema for a data object and a target data format or target data schema for a data object may be identified. A comparison of the source data schema and the target data format or schema may be made to determine what transformations can be performed to transform the data object into the target data format or schema. Code to execute the transformation operations may then be generated. The code may be stored for subsequent modification or execution.

Abstract: A method for managing data using writeable snapshots in a multi-versioned, distributed B-tree comprising nodes distributed over a plurality of servers, includes receiving a transaction request specifying a transaction type, the transaction having a transaction snapshot id, and determining the transaction type. If the transaction type is an update transaction, the method includes determining a node to update, which is defined by a node snapshot id, and if the transaction snapshot id is greater that the node snapshot id, the method copies the node and updates the copy to create a writeable snapshot, assigns the transaction snapshot id as a node snapshot id of the copy, and places a pointer from the node to the copy.

Abstract: A method for managing data using writeable snapshots in a multi-versioned, distributed B-tree comprising nodes distributed over a plurality of servers, includes receiving a transaction request specifying a transaction type, the transaction having a transaction snapshot id, and determining the transaction type. If the transaction type is an update transaction, the method includes determining a node to update, which is defined by a node snapshot id, and if the transaction snapshot id is greater that the node snapshot id, the method copies the node and updates the copy to create a writeable snapshot, assigns the transaction snapshot id as a node snapshot id of the copy, and places a pointer from the node to the copy.