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Devart

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1,138 reviews
  • 183 profiles
  • 31 categories
Average star rating
4.6
Serving customers since
1997
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ODBC Driver for Hubspot

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Devart ODBC Driver for HubSpot is a high-performance connectivity tool with enterprise-level features for accessing HubSpot from ODBC-compliant reporting, analytics, BI, and ETL tools on both 32-bit and 64-bit Windows. Our ODBC driver fully supports standard ODBC API functions and data types and enables easy access to live HubSpot data from anywhere.

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dotConnect for BigCommerce

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dotConnect for BigCommerce is an ADO.NET provider for working with BigCommerce data through the standard ADO.NET or Entity Framework interfaces. It allows you to easily integrate BigCommerce data into your .NET applications, and integrate BigCommerce services with widely used data-oriented technologies. dotConnect for BigCommerce has the same standard ADO.NET classes as other standard ADO.NET providers: BigcommerceConnection, BigcommerceCommand, BigcommerceDataAdapter, BigcommerceDataReader, BigcommerceParameter, etc. This allows you quickly get started with it and eliminates the need to study any BigCommerce data access specificities.

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Zoho CRM Excel Add-In by Devart

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Devart Excel Add-in for Zoho CRM allows you to connect Microsoft Excel to Zoho CRM, quickly and easily load data from Zoho CRM to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Zoho CRM. It enables you to work with Zoho CRM 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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Zendesk Excel Add-In by Devart

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Devart Excel Add-in for Zendesk allows you to connect Microsoft Excel to Zendesk, quickly and easily load data from Zendesk to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Zendesk. It enables you to work with Zendesk 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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InterBase Python Connector

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The InterBase Python Connector is a robust and efficient solution designed to facilitate seamless interaction between Python applications and InterBase databases. Fully implementing the Python DB API 2.0 specification, this connector enables developers to perform create, read, update, and delete operations on InterBase-stored data with ease. Distributed as a wheel package, it supports multiple platforms, including Windows, macOS, and Linux, ensuring broad compatibility and straightforward deployment. Key Features and Functionality: - High Performance: The connector allows for batch processing of multiple update statements, significantly improving execution times and overall application performance. - Secure Communication: It supports InterBase's Over-the-Wire encryption, ensuring that data transmitted between the application and the database remains secure. - Comprehensive Compatibility: Compatible with all InterBase versions from 4.2 onwards, including Developer, Embedded IBLite, Embedded IBToGo, Desktop, and Server editions. It also supports Python versions from 3.7 to 3.13. - Cross-Platform Support: Available for Windows , macOS , and Linux , catering to diverse development environments. - Unicode Compliance: The connector is fully Unicode-compliant, enabling the retrieval and updating of multilingual data across various character encodings, such as Chinese, Cyrillic, and Hebrew. - Extensive Data Type Support: It supports all InterBase and Python data types, offering additional options to control data type mapping between the two, ensuring flexibility in data handling. Primary Value and User Solutions: The InterBase Python Connector addresses the critical need for a reliable and efficient interface between Python applications and InterBase databases. By providing high-performance data operations, secure communication channels, and broad compatibility across platforms and database versions, it empowers developers to build robust applications without the complexities of database connectivity. Its Unicode compliance and comprehensive data type support further ensure that applications can handle diverse datasets seamlessly, making it an invaluable tool for developers working in multilingual and varied data environments.

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QuickBooks Online Excel Add-In by Devart

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Devart Excel Add-in for QuickBooks Online allows you to connect Microsoft Excel to QuickBooks Online, quickly and easily load data from QuickBooks Online to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to QuickBooks Online. It enables you to work with QuickBooks Online 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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Firebird Python Connector

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The Firebird Python Connector is a robust and user-friendly solution designed to facilitate seamless interaction between Python applications and Firebird databases. Fully implementing the Python DB API 2.0 specification, this connector enables developers to perform create, read, update, and delete operations efficiently. Distributed as a wheel package, it supports multiple platforms, including Windows, macOS, and Linux, ensuring broad compatibility and ease of deployment. Key Features and Functionality: - High Performance: Supports batch processing of multiple update statements, enhancing execution speed and overall application performance. - Secure Communication: Utilizes Firebird's Over-the-Wire (OTW encryption to secure data during transmission, safeguarding sensitive information. - Comprehensive Compatibility: Compatible with all Firebird versions from 1.x to 5.x and Python versions from 3.7 to 3.13, ensuring flexibility across various development environments. - Platform Support: Available for Windows (32-bit and 64-bit, macOS (64-bit and ARM, including Apple M1 and M2, and Linux (64-bit, catering to diverse system requirements. - Unicode Compliance: Handles multilingual data seamlessly, supporting various character encodings such as Chinese, Cyrillic, and Hebrew, which is essential for global applications. - Extensive Data Type Support: Supports all Firebird and Python data types, with options to control data type mapping between the two, providing flexibility in data handling. - Connection Pooling: Enhances application performance and scalability by reusing database connections, reducing the overhead associated with establishing new connections. Primary Value and Problem Solved: The Firebird Python Connector addresses the critical need for a reliable and efficient interface between Python applications and Firebird databases. By offering high performance, secure communication, and broad compatibility, it simplifies database operations, reduces development time, and enhances application scalability. Its support for multiple platforms and Unicode compliance ensures that developers can build versatile and globally accessible applications without worrying about data integrity or compatibility issues.

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Magento Excel Add-In by Devart

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Devart Excel Add-in for Magento allows you to connect Microsoft Excel to Magento, quickly and easily load data from Magento to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Magento. It enables you to work with Magento 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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HubSpot Python Connector

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The HubSpot Python Connector by Devart is a robust and user-friendly solution designed to facilitate seamless integration between Python applications and HubSpot. It enables developers to perform create, read, update, and delete (CRUD operations on HubSpot data, adhering fully to the Python DB API 2.0 specification. Distributed as a wheel package, it supports both 32-bit and 64-bit Windows platforms, ensuring broad compatibility and ease of installation. Key Features and Functionality: - Standard SQL Syntax Support: The connector allows execution of ANSI SQL statements against HubSpot data, simplifying data manipulation. Simple queries are directly converted to HubSpot API calls, while complex queries are broken down and processed efficiently. - High Performance: With support for connection pooling and local data caching, the connector enhances access speed. It also enables batch processing of multiple update statements, reducing execution time. - Platform Compatibility: Designed for Windows and Windows Server environments, the connector caters to a wide range of development scenarios. - Unicode Compliance: It supports retrieval and updating of multilingual data, accommodating various character encodings such as Chinese, Cyrillic, and Hebrew. - Comprehensive Data Type Support: The connector handles all HubSpot and Python data types, offering options to control data type mapping between the two. Primary Value and User Benefits: The HubSpot Python Connector streamlines the integration of HubSpot data into Python applications, enabling developers to interact with HubSpot as they would with a traditional relational database. By supporting standard SQL syntax and providing high-performance features like connection pooling and local caching, it simplifies data operations and enhances efficiency. Its compatibility with various Windows platforms and support for multiple languages through Unicode compliance make it a versatile tool for developers aiming to build robust, data-driven applications with HubSpot.

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Devart Reviews

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Star Rating
892
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9
FI
Frederik I.
05/28/2026
Validated Reviewer
Review source: Organic

dbForge Studio Makes Database Compare and Data Search Easy

For a non-DB-admin, I find the tools provided in dbForge Studio extremely helpful. My favorite items are the Database compare (helps me with clients in Production and Sandbox), and Find data
Elías A.
EA
Elías A.
Senior Product Designer — Discovery & Software Design · Complexity made simple for B2B, SaaS & Data Tools
05/27/2026
Validated Reviewer
Verified Current User
Review source: Organic

TMetric is an easy to use time tracking app

It´s easy to use, i don´t think about it much but it runs througout the day and gives me visibility on what tasks eat my days most.
Dmytro S.
DS
Dmytro S.
Co-Founder at Syntropy
05/27/2026
Validated Reviewer
Verified Current User
Review source: Organic

Effortless Time Tracking and Reporting with TMetric for Marketing Teams

As a marketing lead, keeping track of time across multiple campaigns, client projects, and team collaborations is critical. TMetric makes this effortless. The interface is clean and intuitive. I love how seamlessly it integrates with Asana, and the reporting features give me a clear picture of where our time is actually going. It's helped us make smarter decisions about resource allocation and project prioritization. For a fast-moving marketing team, that kind of visibility is invaluable.

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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