International Business Machines Corporation

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International Business Machines Coproartion

Namik Hrle

Daniel Martin

Peter Bendel

Oliver Draese

Felix O Beier

James Zu-Chia Teng

Ruiping Li

Knut Stolze

Andreas Brodt

Oliver Schiller

Nicole Finnie

James Z Teng

Oliver Benke

Maryela Evelin Weihrauch

Chandrasekaran Mohan

James D Spyker

Thomas F Boehme

Johannes Schuetzner

Yongfeng Yao

Tianchao Li

Dinesh C Verma

Martin Oberhofer

Curt Lee Cotner

Donna N Dillenberger

Oliver Koeth

Matthias Tschaffler

Jens Mueller

Andreas Lohrer

Thomas Ritter

Guogen Zhang

Einar Lueck

Roland Seiffert

Sunil Sarin

Vassil Radkov Dimov

Joachim Rese

Claus Kempfert

Jens Müller

Robert S Muse

Amit Bendakovsky

Georg K Mayer

Kevin Pelletier

Vijayshankar Raman

Inderpal Singh Narang

James Alan Ruddy

Julie Ann Watts

Jeffrey William Josten

Oliver Augenstein

Michael Jeffrey Winer

Holger Karn

Torsten Steinbach

Akira Shibamiya

Johannes S Kern

Dennis Butterstein

Michael Reichert

Andreas Uhl

Guenter Briam

Andreas Maier

Charles Roy Bonner

Thomas Majithia

Christian Michel

Stephen Walter Turnbaugh

Christian Wilhelm Paul Hoerst

Norbert Heck

Huiyan Roy

Thorsten Steinbach

A method for executing a query on a target database against the most recent source data is disclosed. The method comprises maintaining linked—i.e., at least partially synchronized—databases comprising a source and a target database. The method comprises receiving a direct query against a table in the target database, the query comprising a request for using the most recent source data and requesting by the target database from the source database a status about latest data regarding the table. Upon the status indicating that data in the table do not correspond to the most recent data, the method comprises waiting up to a predefined time period for the most recent data of the table to be synchronized from the source database to the target database, and upon the data of the table not being synchronized within the predefined time period, the method comprises issuing a timeout signal.

Query execution on a replicated database with most recent data

In an approach, a primary data center is provided including primary source and primary target database systems, where a function is activated causing the primary target database system to: include a copy of data and receive analysis queries from the primary source database system; and execute the analysis queries on data. A processor, in response to detecting a failure in the primary source database system: offloads queries intended for the primary source database system to a secondary source database system of a secondary data center also including a secondary target database system and a copy of data, where the function is deactivated. A processor, responsive to the primary target database system being available: receives analysis queries, processed by the secondary source database system, of the offloaded queries; and copies data to the secondary target database system. A processor causes the function to be activated in the secondary data center.

Operating a data center

Creating at a target database system, a target table and a history table each having a set of attributes of a source table in addition to at least one time attribute, wherein the time attribute of a record indicates the time when the record is valid. Receiving a request for applying a change of the source table to the target table. The request comprises a time value generated by the source database system indicating a time of the change. The change to the target table and the time value may be assigned to the time attribute of the current version and previous version of the record. The previous version of the record may be stored in the history table. The target table and the history table may be used to process a redirected query comprising a selection criterion on the time attribute.

Maintaining at a target database system a copy of a source table of a source database system

An example operation may include one or more receiving an entry at a blockchain-as-a-service (Baas) provider, determining whether the entry satisfies a first set of policies, and controlling placement of the entry into a first queue when the first set of policies is satisfied and into a second queue when the first set of policies is not satisfied, wherein the first queue is to store confirmed entries to be submitted for consensus without validation and the second queue is to store pending entries that require validation before consensus.

Information management in a decentralized database including a fast path service

An example operation may include one or more of hosting a first virtual node in a blockchain-as-a-service (Baas) provider, hosting a second virtual node in the Baas provider, and controlling transmission of information between the first virtual node and the second virtual node along an internal signal path of the Baas provider, wherein the information corresponds to a block in a blockchain that includes an entry for the first and second virtual nodes.

A computer-implemented method for operating a database management system which includes a source database and a target database. A database management system is configured for asynchronously replicating data changes of the source database to the target database. The database management system receiving a request to perform a database statement. The method can identify the most recently committed one of a plurality of transactions having been committed in the source database before the receiving of the request. Identifying repeatedly the one of the plurality of transactions having been replicated most recently to the target database. Execution of the requested statement in the target database is delayed until an evaluation of the repeatedly identified most recently replicated transaction returns that the identified most recently committed transaction has been replicated to the target database. After the delaying execution, the method executes the requested statement in the target database.

Database management system and method of operation

An example operation may include one or more of determining data at a first node satisfies a condition, obtaining a pointer to a shared storage area for the data, controlling generation of a block including the pointer, and appending the block to a blockchain without the data, wherein the first node corresponds to first virtual node hosted by blockchain-as-a-service (Baas) provider and wherein the first virtual node receives the data from a network coupled to the Baas provider.

A method, system and computer program product for providing consolidated access to data of a plurality of source databases. Tables of each of the source databases are replicated to a shared accelerator. The source DBMSs are configured to dispatch queries to the accelerator for accelerating query execution. The accelerator is configured such that the replicated tables can only be accessed by the source DBMS having provided said tables for executing a dispatched query. A user can select one of the source DBMSs to act as a consolidated DBMS&#x2014;C-DBMS. The C-DBMS provides the consolidated access. The user is enabled to select tables managed by another one of the DBMSs. In response to receiving the selection of the tables, the accelerator is re-configuring such that the C-DBMS is granted access also to the copies of the selected tables in the accelerator.

Accelerator based data integration

An aggregate is generated. Upon receiving a second query comprising a filter criterion, a determination is made as to whether at least a threshold number of previous first queries comprises a similar filter criterion, and if so generating an aggregate using the similar filter criterion as an aggregation criterion, such that future queries comprising the similar filter criterion are satisfied by the aggregate.

Demand-driven dynamic aggregate

The present disclosure relates to a method for processing queries in a database system having a first database engine and a second database engine. The method includes: encrypting at least one predefined column of a first instance of a first table, resulting in a second instance of the first table containing at least part of the data of the first table in encrypted format. It may be determined whether to execute a received query in the first database engine on the first instance of the first table or in the second database engine on the second instance of the first table, where the determination involves a comparison of the query with encryption information.

Transparent analytical query accelerator over encrypted data

A method, a computer program product and a computer system are provided. Attribute value information contains at least a minimum value representing a smallest value of a first attribute and a maximum value representing a largest value of the first attribute, thereby defining a first range of values of the first attribute. A received query against a data table requests one or more values of at least the first attribute that are covered by the first range of values. The attribute value information may be used for selecting a data block of the data table as a candidate potentially including at least part of the requested one or more values and scanning the data block. In response to determining that the data block does not include the one or more requested values, the attribute value information may be updated accordingly.

Self-optimizing value range synopsis in analytical databases

A distributed database system (or federated database system) where a catalogue is used to store metadata descriptive of data containers for the constituent database system(s) and/or accelerator system(s) of the federated database. In response to the generation of the trigger signal corresponding to a database definition language (DDL) statement, the accelerator system updates metadata in the catalogue.

Distributed system with accelerator and catalog

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Boeblingen, Germany

Namik Hrle