Abstract: According to an aspect, a database management system (DBMS) is operated to perform data replication. The DBMS includes a source database and a target database. The source database includes a plurality of first tables respectively comprising one or more first columns, and the target database includes a plurality of second tables respectively comprising one or more second columns. Each of multiple ones of the first columns is mapped to one of the second columns, and each one of the second columns is adapted to store replicated data changes of the first column mapped to the second column. Each of the second columns has an assigned update time, the update time being a moment in time when the second column most recently received incremental data changes from its mapped first column. The DBMS operates to process requested database statements while providing data replication.

Abstract: A first request may be received to update a first set of values. The first set of values may be stored at a first location within a first data page of a database. The first location may be read-only. In response to the receiving of the first request, a first set of records may be inserted into a second data page. The first set of records may include the update of the first set of values. In response to the inserting, a forward pointer may be stored in the first data page that points to the first set of records on the second data page. One or more committed values may be identified on the second data page. In response to the identifying, the one or more committed values may be merged from the second data page to a third data page.

Abstract: According to one embodiment of the present invention, a method for processing a query in a column database is provided. The method for analyzing test results may include a computer, associating a first set of metadata values with a set of records in a table, wherein each record has an associated state indicated by a metadata value. The method may further include the computer receiving a query to return one or more records of the set of records. The method may further include the computer determining that one or more records in the set of records satisfies the query. The method may further include the computer determining whether at least a first record in the one or more records that satisfies the query is in a returnable state based, at least in part, on the metadata value.

Abstract: According to one embodiment of the present invention, a method for processing a query in a column database is provided. The method for analyzing test results may include a computer, associating a first set of metadata values with a set of records in a table, wherein each record has an associated state indicated by a metadata value. The method may further include the computer receiving a query to return one or more records of the set of records. The method may further include the computer determining that one or more records in the set of records satisfies the query. The method may further include the computer determining whether at least a first record in the one or more records that satisfies the query is in a returnable state based, at least in part, on the metadata value.

Abstract: According to an aspect, a database management system (DBMS) is operated to perform data replication. The DBMS includes a source database and a target database. The source database includes a plurality of first tables respectively comprising one or more first columns, and the target database includes a plurality of second tables respectively comprising one or more second columns. Each of multiple ones of the first columns is mapped to one of the second columns, and each one of the second columns is adapted to store replicated data changes of the first column mapped to the second column. Each of the second columns has an assigned update time, the update time being a moment in time when the second column most recently received incremental data changes from its mapped first column. The DBMS operates to process requested database statements while providing data replication.

Abstract: A first request may be received to update a first set of values. The first set of values may be stored at a first location within a first data page of a database. The first location may be read-only. In response to the receiving of the first request, a first set of records may be inserted into a second data page. The first set of records may include the update of the first set of values. In response to the inserting, a forward pointer may be stored in the first data page that points to the first set of records on the second data page. One or more committed values may be identified on the second data page. In response to the identifying, the one or more committed values may be merged from the second data page to a third data page.

Abstract: A method includes scanning multiple incoming database transaction requests. Each transaction includes one or more operations. Operations are clustered into a set of combined operations based on type of operation constraints. Log records are prepared and written for re-performing operations upon system failures, and for undoing operations upon an operation or a transaction failing to be processed fully. Each set of combined operations are performed within a thread. Each update operation is marked for a transaction within which the update operation belongs. Recoverable update operations belonging to a plurality of transactions are performed within a single logical thread of execution.

Abstract: Described herein are techniques for supporting bi-temporal data in a key value cache system. An embodiment provides bi-temporal data as the basic functionality of a key value cache system. An embodiment provides a redesign of the core data structures of a key value cache system, adds bi-temporal data storage in the key value hashing structure, and provides a temporality-aware memory space manager. Embodiments can achieve the same performance as current key value cache systems for regular queries (that is, the queries that only access the current versions of data) while supporting bi-temporal data.

Abstract: Embodiments relate to database systems. An aspect includes deferring row insert operations until occurrence of a triggering event. One method includes receiving a row insert for a tuple into a column group store table, where the tuple includes one or more tuplets and each of the tuplets corresponds to a column group in the column group store table. The method also includes copying at least one of the tuplets into an insert buffer that is specific to one of the column groups in the column group store table. The method also includes deferring the row insert into the column group store table until an occurrence of one or more triggering events. The method also includes flushing the row insert into storage associated with the column group store table, in response to the occurrence of the one or more triggering events.

Abstract: A first request may be received to update a first set of values. The first set of values may be stored at a first location within a first data page of a database. The first location may be read-only. In response to the receiving of the first request, a first set of records may be inserted into a second data page. The first set of records may include the update of the first set of values. In response to the inserting, a forward pointer may be stored in the first data page that points to the first set of records on the second data page. One or more committed values may be identified on the second data page. In response to the identifying, the one or more committed values may be merged from the second data page to a third data page.

Abstract: A first request may be received to update a first set of values. The first set of values may be stored at a first location within a first data page of a database. The first location may be read-only. In response to the receiving of the first request, a first set of records may be inserted into a second data page. The first set of records may include the update of the first set of values. In response to the inserting, a forward pointer may be stored in the first data page that points to the first set of records on the second data page. One or more committed values may be identified on the second data page. In response to the identifying, the one or more committed values may be merged from the second data page to a third data page.

Abstract: A first request may be received to update a first set of values. The first set of values may be stored at a first location within a first data page of a database. The first location may be read-only. In response to the receiving of the first request, a first set of records may be inserted into a second data page. The first set of records may include the update of the first set of values. In response to the inserting, a forward pointer may be stored in the first data page that points to the first set of records on the second data page. One or more committed values may be identified on the second data page. In response to the identifying, the one or more committed values may be merged from the second data page to a third data page.

Abstract: A first request may be received to update a first set of values. The first set of values may be stored at a first location within a first data page of a database. The first location may be read-only. In response to the receiving of the first request, a first set of records may be inserted into a second data page. The first set of records may include the update of the first set of values. In response to the inserting, a forward pointer may be stored in the first data page that points to the first set of records on the second data page. One or more committed values may be identified on the second data page. In response to the identifying, the one or more committed values may be merged from the second data page to a third data page.

Abstract: A method includes setting, by an update processor, a write latch in a first data structure associated with an object. The first data structure is copied to a storage structure. A history tuple sequence number (TSN) of the first data structure is set to point to a TSN of the copied first data structure. The version identifier is set to point to a transaction identification for the object. Data portions are updated for the first data structure. The version identifier is read from the first data structure. It is determined whether the version identifier of the first data structure is visible for a transaction including isolation requirements. If version identifier of the first data structure is visible, the first data structure is accessed and it is determined whether the version identifier of the first data structure changed since starting the transaction.

Abstract: Provided are techniques for using parallel inserts to insert into a column store. A list of sub-ranges for a columnar table is created. A change statement for one or more rows to be inserted into the columnar table is received. For each of the received change statements, a sub-range from the list of sub-ranges is identified and data is serially inserted into the identified sub-range of the columnar table, while allowing parallel processing of each change statement for different sub-ranges of the columnar table.

Abstract: Embodiments of a system are described. In one embodiment, the system is a device for performing operations and supporting transactions. The device is configured to receive a transaction comprising a command and data. The device writes the data to a transaction manager on a persistent memory device. The transaction manager also maintains a status of the transaction and reference to entries within memory that are manipulated by the transaction. The device also creates an in-memory log of the transaction in a first hash directory. The device then commits a copy of the first hash directory to a second hash directory maintained on a persistent memory device.

Abstract: A method includes scanning multiple incoming database transaction requests. Each transaction includes one or more operations. Operations are clustered into a set of combined operations based on type of operation constraints. Log records are prepared and written for re-performing operations upon system failures, and for undoing operations upon an operation or a transaction failing to be processed fully. Each set of combined operations are performed within a thread. Each update operation is marked for a transaction within which the update operation belongs. Recoverable update operations belonging to a plurality of transactions are performed within a single logical thread of execution.

Abstract: A method includes logically organizing, by an object hierarchy processor, data objects in a first hierarchy. A portion of the data objects in the first hierarchy logically includes groupings of other data objects. The object hierarchy processor physically organizes the data objects across two or more types of memory in a second hierarchy. Another portion of the data objects in the second hierarchy physically includes groupings of other data objects. Groupings of the data objects in the second hierarchy are dynamically moved across the two or more types of memory. Levels of access of the data objects are tracked using a data structure that maps groupings of the data objects in the first hierarchy onto metadata information including combined access frequencies of the data objects, and current number of accessors to the data objects, in each grouping of the data objects.

Abstract: Provided are techniques for using parallel inserts to insert into a column store. A list of sub-ranges for a columnar table is created. A change statement for one or more rows to be inserted into the columnar table is received. For each of the received change statements, a sub-range from the list of sub-ranges is identified and data is serially inserted into the identified sub-range of the columnar table, while allowing parallel processing of each change statement for different sub-ranges of the columnar table.

Abstract: Provided are techniques for using parallel inserts to insert into a column store. A list of sub-ranges for a columnar table is created. A change statement for one or more rows to be inserted into the columnar table is received. For each of the received change statements, a sub-range from the list of sub-ranges is identified and data is serially inserted into the identified sub-range of the columnar table, while allowing parallel processing of each change statement for different sub-ranges of the columnar table.