Microsoft SQL Server Analysis Services (SSAS) 7.0 to 2000 (Repository) Microsoft SQL Server Analysis Services (SSAS) 2016 (File) Microsoft Office Visio UML (via UML 1.x XMI) Microsoft Office Visio Database Diagram (via ERX)
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Microsoft Azure SQL Data Warehouse (via JDBC) IDERA ER/Studio Business Architect (via DM1) IBM Rational System Architect (SA) 10.4 to 11.x (Encyclopedia)
MAGICDRAW EXCEL IMPORT SOFTWARE
IBM Rational Software Modeler (RSM) (via Rose MDL) IBM Rational Software Architect (RSA) (via UML 2.x XMI) IBM Rational Software Architect (RSA) (via Rose MDL) IBM Rational Rose XDE Developer (via Rose MDL) IBM InfoSphere Warehouse - InfoSphere Data Architect IBM InfoSphere Federation Server (via JDBC) IBM DB2 Universal Database (UDB) (via JDBC) IBM Cognos Framework Manager (FM) for ReportNet MapR Hadoop Hive Database (HCatalog via JDBC)ĬA Component Modeler 4.x (via UML 1.x XMI)ĬA COOL:Xtras Mapper (TerrainMap for Db2)ĭatabase SQL Data Definition Language (DDL)įile System (CSV, Excel, XML, JSON, Avro, Parquet, ORC, COBOL Copybook) Hortonworks Hadoop Hive Database (HCatalog via JDBC) Complete any requirements as appropriate before proceeding.Īctian Vector (Vectorwise) Database (via JDBC)Īmazon Web Services (AWS) Glue ETL - Beta BridgeĪmazon Web Services (AWS) RedShift Database (via JDBC)Īpache Hadoop Hive Native bridges include:Īpache Hadoop Hive Database (Hive Metastore via JDBC)Īpache Hadoop Hive Database (HCatalog via JDBC)Īpache Hadoop Hive Database (Web Hcatalog)Īpache Hadoop HBase NoSQL Database (Java API)Ĭloudera Enterprise Hadoop Hive Database (HCatalog via JDBC) Note: Read the information displayed in the tip text area on the Source and Destination pages of the Import from External Format and Export to External Format dialogs carefully. (10.0.1) bridges that are currently available in erwin Data Modeler (as of Release 2020 R1):
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* Disjunction reusing the blocksOrRequirements and constraintBlocks patterns and the negation of dependencies.The following table lists the Meta Integration Technology, Inc. Returns classes with 'Block' or 'Requirement' SysML stereotype, or classes with 'Constraint' SysML stereotype that are not involved as part of a dependency This way certain patterns can be optimized to be run with the backend that match their characteristics the best. Allow the user to mark conditions to be executed solely by the Rete engine, while others will be executed using local search. * *Hybrid backend*: Combines the positive aspects of Rete and LS based querying. More information about the Rete and LS algorithms can be found The search is executed based on a search plan that selects the first node to be matched and defines the order in which individual query constraints are evaluated. * *Local search backend*: With the local-search backend, the search is restarted from scratch each time a query evaluation is requested. NOTE: Queries in the MagicDraw plug-in utilize the Rete backend More information about the Rete algorithm can be found. This network serves as a cache that is maintained on the fly as the model instance is modified. * *Incremental backend based on Rete networks*: Stores individual constraints of queries along with their result sets in a graph network (Rete network). The VIATRA Query Framework features multiple query evaluation backend implementations. = Measured query engine backend implementations Sizes of each used model instance (number of total EObjects) This way the size of the model does not hinder the MagicDraw UI unnecessarily. Each added copy is on a new structure level, resulting in deep model hierarchy. These instances are created via copy-pasting the work packages of the original TMT model.
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The benchmark is executed on various sized instances of the (TMT) model. * *Memory overhead of VIATRA:* Memory overhead added by initializing a VIATRA query engine over a model instance, and executing a given query on it.ĭuring the execution of the benchmark the following environment was used (as a Jenkins slave on ): * *Overall memory usage:* Overall allocated memory of the measured MagicDraw instance after querying. * *Query result set size:* Size of the result set of a selected query over the given model instance. * *Query result calculation time*: The time it takes to fetch the result set of a given query over an already initialized VIATRA query engine. * *Initialization time*: The time it takes to initialize the VIATRA query framework on a loaded model. During the benchmark a properties of various queries are measured, while they are being executed using a number of query engine implementations. The measurements are taking place in a MagicDraw-based ecosystem.
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The goal of this benchmark is to measure the query speed and memory overhead of the using organic SysML model instances. ? github-wiki-see.page does not render asciidoc.