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Devart

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1,148 reviews
  • 183 profiles
  • 31 categories
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4.6
Serving customers since
1997
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Shopify Excel Add-In by Devart

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Devart Excel Add-in for Shopify allows you to connect Microsoft Excel to Shopify, quickly and easily load data from Shopify to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Shopify. It enables you to work with Shopify data like with usual Excel worksheets, easily perform data cleansing and de-duplication, and apply all the Excel's powerful data processing and analysis capabilities to these data.

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DB2 Excel Add-In by Devart

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Devart Excel Add-in for DB2 allows you to connect Microsoft Excel to DB2, quickly and easily load data from DB2 to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to DB2. It enables you to work with DB2 data like with usual Excel worksheets, easily perform data cleansing and de-duplication, and apply all the Excel's powerful data processing and analysis capabilities to these data.

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Dynamics 365 Python Connector

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The Dynamics 365 Python Connector is a robust solution designed to facilitate seamless integration between Python applications and Dynamics 365 Customer Engagement (formerly Dynamics CRM. It enables developers to perform create, read, update, and delete (CRUD operations on Dynamics 365 data using standard SQL syntax, simplifying data manipulation and enhancing productivity. Fully compliant with the Python DB API 2.0 specification, this connector is available as a wheel package compatible with Windows, macOS, and Linux platforms. Key Features and Functionality: - Standard SQL Syntax Support: Execute SQL statements against Dynamics 365 data as you would with relational databases. Simple queries are directly converted to Dynamics 365 API calls, while complex queries are transformed and processed efficiently. - High Performance: Features connection pooling and local data caching to boost access speed. Supports batch processing of multiple update statements to enhance execution time. - Cross-Platform Compatibility: Available for Windows (32-bit and 64-bit, macOS (64-bit and ARM, including Apple M1 and M2, and Linux (64-bit. - Unicode Compliance: Retrieve and update multilingual data seamlessly, regardless of character encoding, supporting languages such as Chinese, Cyrillic, Hebrew, and more. - Comprehensive Data Type Support: Supports all Dynamics 365 and Python data types, offering options to control data type mapping between them. Primary Value and User Benefits: The Dynamics 365 Python Connector addresses the challenge of integrating Python applications with Dynamics 365 by providing a straightforward, high-performance solution. By supporting standard SQL syntax and offering features like connection pooling and local caching, it simplifies data operations and enhances efficiency. Its cross-platform support ensures that developers can work in their preferred environments without compatibility concerns. Overall, this connector streamlines the development process, allowing for more effective and efficient interaction with Dynamics 365 data.

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Oracle Excel Add-In by Devart

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Devart Excel Add-in for Oracle allows you to connect Microsoft Excel to Oracle, quickly and easily load data from Oracle to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Oracle. It enables you to work with Oracle data like with usual Excel worksheets, easily perform data cleansing and de-duplication, and apply all the Excel's powerful data processing and analysis capabilities to these data.

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FreshBooks Excel Add-In by Devart

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Devart Excel Add-in for Freshbooks allows you to connect Microsoft Excel to Freshbooks, quickly and easily load data from Freshbooks to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Freshbooks. It enables you to work with Freshbooks data like with usual Excel worksheets, easily perform data cleansing and de-duplication, and apply all the Excel's powerful data processing and analysis capabilities to these data.

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dotConnect for Zoho CRM

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dotConnect for Zoho CRM is a high-end ADO.NET data provider that helps access and manage Zoho CRM data through the standard ADO.NET or EF Core interfaces. Thus, it helps you easily integrate this data into .NET applications. Our data provider works with the standard ADO.NET classes. This allows you to get started quickly and eliminates the need to study any specifics of Zoho CRM. What's more, our provider utilizes its own SQL engine for data retrieval, which makes the entire process even more efficient. - Broad compatibility with .NET platforms, including ASP.NET Core, Blazor, MAUI, .NET Framework, etc. - ORM support: EF Core, Dapper, NHibernate, LinqConnect, etc. - Full compliance with ADO.NET - SSL, SSH, proxy servers, and HTTP tunnels support - Integration with Visual Studio and design-time support - Regular updates and detailed documentation

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BigCommerce Python Connector

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The BigCommerce Python Connector is a robust and user-friendly solution designed to facilitate seamless integration between Python applications and BigCommerce stores. By fully implementing the Python DB API 2.0 specification, it enables developers to perform create, read, update, and delete operations on BigCommerce data using standard SQL syntax. This connector is distributed as a wheel package compatible with Windows, macOS, and Linux platforms. Key Features and Functionality: - Standard SQL Syntax Support: Allows execution of SQL statements against BigCommerce data, with simple queries directly converted to API calls and complex queries processed through an embedded SQL engine. - High Performance: Features connection pooling and local data caching to enhance access speed, and supports batch processing of multiple update statements to improve execution time. - Cross-Platform Compatibility: Available for Windows , macOS , and Linux , ensuring broad usability across different operating systems. - Unicode Compliance: Supports retrieval and updating of multilingual data, accommodating various character encodings such as Chinese, Cyrillic, and Hebrew. - Comprehensive Data Type Support: Handles all BigCommerce and Python data types, offering options to control data type mapping between them. Primary Value and User Solutions: The BigCommerce Python Connector streamlines the integration of BigCommerce data into Python applications, enabling developers to interact with e-commerce data using familiar SQL syntax. This reduces the complexity associated with direct API interactions and accelerates development processes. By supporting multiple platforms and ensuring high performance through features like connection pooling and local caching, the connector enhances efficiency and scalability for businesses managing their BigCommerce stores programmatically.

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Zoho Books Excel Add-In by Devart

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Devart Excel Add-in for Zoho Books allows you to connect Microsoft Excel to Zoho Books, quickly and easily load data from Zoho Books to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Zoho Books. It enables you to work with Zoho Books data like with usual Excel worksheets, easily perform data cleansing and de-duplication, and apply all the Excel's powerful data processing and analysis capabilities to these data.

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Adobe Commerce SSIS Components by Devart

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Devart SSIS Data Flow Components for Adobe Commerce allow you to integrate Adobe Commerce data with other databases and cloud applications via SQL Server Integration Services (SSIS). They include optimized Adobe Commerce Source, Adobe Commerce Destination, and Adobe CommerceLookup components and provide their own Adobe Commerce Connection Manager with lots of Adobe Commerce-specific connectivity features. - Export data from Adobe Commerce to various sources - Import XML, CSV, and other files to Adobe Commerce - Automate Adobe Commerce integration via SSIS Data Flow tasks - Migrate from/to Adobe Commerce using SSIS - Synchronize Adobe Commerce with SQL Server or other data sources - Integrate various data sources with Adobe Commerce via SSIS

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Devart Reviews

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Alina S.
AS
Alina S.
Product Marketing Manager | Bridging Product, Marketing & Sales through positioning and messaging
07/27/2026
Validated Reviewer
Review source: Organic

Effortless Data Integration with Skyvia

I love how easy it is to change things in Skyvia. Adding a field or adjusting the schedule doesn't turn into a separate project, which really saves me time. The run history is also incredibly useful; I can quickly check if everything is completed without having to open five different tools. Additionally, Skyvia has been easier for us to manage compared to what we were using before, which required more upkeep. The initial setup was straightforward, and the first scheduled load was running by that afternoon.
TM
Tom M.
07/20/2026
Validated Reviewer
Review source: Organic

Easy Setup & Cost-Effective for Data Integration

I really appreciate Skyvia being code-free and easy to set up and use. The price is also a great advantage. I find the data transformation and replication features particularly valuable. Plus, the initial setup was easy peasy.
Jürgen K.
JK
Jürgen K.
07/09/2026
Validated Reviewer
Verified Current User
Review source: Organic
Translated Using AI

dbForge Studio: Familiar like SSMS, but with a powerful debugger and top comparison features

I have been working with Microsoft SQL Server for decades, and for just as long with Microsoft SQL Server Management Studio. For about two years now, I have also been using dbForge Studio for SQL Server – and the tool has really convinced me. What I particularly like: The basic structure is heavily oriented towards SSMS. Anyone familiar with it will quickly find their way around dbForge. At the same time, dbForge offers many functions that provide real added value in the everyday life of database development and management. A major advantage for me is the integrated debugger, especially because corresponding debugging functions are no longer available in newer SSMS versions. I also find the schema and data comparison very strong. This allows database structures, table contents, and especially stored procedures to be compared and synchronized very comfortably between different databases. This is extremely helpful, especially when working with development, test, and production databases. The graphical interfaces for these comparison and synchronization functions are also very well done. You can easily understand differences, select them specifically, and adopt them in a controlled manner. This saves time and reduces errors. Overall, dbForge Studio is a real enrichment for me compared to SSMS. It feels familiar but significantly expands the range of functions in many important areas. For professional SQL Server development and database maintenance, it is, in my view, a highly recommendable tool.

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HQ Location:
Wilmington, Delaware, USA

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@DevartSoftware

Streamline complex data tasks and increase productivity with our expert solutions

Since its founding in 1997, Devart has been working on simplifying and enhancing data workflows for both individual professionals and teams, including enterprise-level organizations from the Fortune 100 list. Currently, Devart is one of the leading developers of data integration, backup, management, and connectivity solutions, as well as database tools for major database management systems and cloud platforms.

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Year Founded
1997
Website
www.devart.com