Create and deliver personalized experiences across digital properties at scale
Build engaging websites with intuitive web content management
Leverage a complete UI toolbox for web, mobile and desktop development
Build, protect and deploy apps across any platform and mobile device
Build mobile apps for iOS, Android and Windows Phone
Rapidly develop, manage and deploy business apps, delivered as SaaS in the cloud
Automate UI, load and performance testing for web, desktop and mobile
Host, deploy and scale Node.js, Java and .NET Core apps on premise or in the cloud
Optimize data integration with high-performance connectivity
Automate decision processes with a no-code business rules engine
Globally scale websites with innovative content management and infrastructure approaches
Content-focused web and mobile solution for empowering marketers
Faster, tailored mobile experiences for any device and data source
UX and app modernization to powerfully navigate today's digital landscape
Fuel agility with ever-ready applications, built in the cloud
As recently as our Connect for ADO.NET 3.2 release, we introduced support for bulk load operations across all of our providers. We are already getting excellent feedback on what we hoped would be our most prominent features, namingly
The DDTek.Data.Common.DbBulkCopy* objects which act as an extension for programmers who want to extend their usage of the common programming model and provider factories. Check here for functional details on a DbBulkCopy, DbBulkCopyColumnMapping (and more) objects. If you've used bulk copy in in ADO.NET this is a nice extension of the established pattern in ADO.NET where SqlBulkCopy originally blazed the trail.
Just as popular is our ability to consume standard CSV files that be either generated/processed automatically (CsvWriter and CsvReader respectively) or by an outside tool using our published schema as a guide. Although, in hindsight, an obvious point of integration, we probably didn't do as a good a job in making it easy to understand how any outside tool would could understand the decisions we took on how we map specific database data types to our common CSV data type.
So to meet this need, I am publishing a range of tables below that show how each database type, or DbType maps to our XML Schema 'dataType' facet.
View all posts from Jonathan Bruce on the Progress blog. Connect with us about all things application development and deployment, data integration and digital business.
Copyright © 2016, Progress Software Corporation and/or its subsidiaries or affiliates.
All Rights Reserved.
Progress, Telerik, and certain product names used herein are trademarks or registered trademarks of Progress Software Corporation and/or one of its subsidiaries or affiliates in the U.S. and/or other countries. See Trademarks or appropriate markings.