Devart
- 189 profiles
- 31 categories
Featured Products
All Products & Services
The Microsoft Access Python Connector by Devart is a robust solution that enables Python applications to interact seamlessly with Microsoft Access databases. Fully implementing the Python DB API 2.0 specification, this connector facilitates efficient create, read, update, and delete operations on Access databases without the need for additional software installations. It supports both .mdb and .accdb file formats, including those from the latest Microsoft Access versions, and is compatible across Windows, macOS, and Linux platforms. Key Features and Functionality: - Direct Connection: Establishes a direct link to Access databases without requiring Microsoft Access or the Access Database Engine Redistributable, simplifying deployment and reducing dependencies. - High Performance: Supports batch processing of multiple update statements, enhancing execution speed and overall performance. - Cross-Platform Support: Available for Windows , macOS , and Linux , ensuring broad compatibility. - Data Type Compatibility: Offers comprehensive support for all Microsoft Access and Python data types, with options to control data type mapping between them. - Read-Only Multi-User Mode: Enables multiple users to read data from a database simultaneously, overcoming the default single-user limitation of Access databases. Primary Value and User Solutions: The Microsoft Access Python Connector addresses the challenges of integrating Python applications with Access databases by eliminating the need for additional drivers or software installations. Its direct connection capability streamlines deployment, especially in multi-user environments, and its cross-platform support ensures flexibility across different operating systems. By enhancing performance through batch processing and providing comprehensive data type support, the connector simplifies database operations, making it an invaluable tool for developers seeking efficient and reliable Access database integration within their Python projects.
Devart Excel Add-in for Google Workspace allows you to connect Microsoft Excel to Google Workspace, quickly and easily load data from Google Workspace to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Google Workspace. It enables you to work with Google Workspace 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.
The MySQL and MariaDB Python Connector by Devart is a robust and user-friendly solution designed to facilitate seamless interaction between Python applications and MySQL or MariaDB database servers. 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. Key Features and Functionality: - Direct Connection: Establishes a direct TCP/IP connection to MySQL or MariaDB servers without requiring a database client library, enhancing data transmission speed. - High Performance: Supports batch processing of multiple update statements, improving execution time and overall application performance. - Fast Deployment: Simplifies deployment across multiple user workstations by eliminating the need to distribute the database client library. - Secure Communication: Ensures encrypted communication using SSL/TLS, SSH tunneling, and HTTP/HTTPS tunneling, safeguarding data integrity and confidentiality. - Platform Support: Compatible with Windows (32-bit and 64-bit, macOS (64-bit, and Linux (64-bit, offering flexibility across different operating systems. - Unicode Compliance: Handles multilingual data seamlessly, supporting various character encodings such as Chinese, Cyrillic, and Hebrew. - Comprehensive Data Type Support: Supports all MySQL/MariaDB and Python data types, with options to control data type mapping between them. Primary Value and Problem Solved: The MySQL and MariaDB Python Connector addresses the need for a reliable, high-performance, and secure method to connect Python applications with MySQL and MariaDB databases. By offering direct connections without the necessity of a client library, it streamlines deployment and enhances data transmission speeds. Its support for secure communication protocols ensures data security, while compatibility across multiple platforms and comprehensive data type support make it a versatile tool for developers working in diverse environments.
dotConnect for SQL Server, formerly known as SQLDirect .NET, is an enhanced data provider for SQL Server that builds on ADO.NET technology and SqlClient to present a complete solution for developing SQL Server-based database applications. As part of the Devart database application development framework, dotConnect for SQL Server offers both high performance native connectivity to SQL Server and a number of innovative database development tools and technologies. dotConnect for SQL Server introduces new approaches for designing application architecture, boosts productivity, and leverages database application implementation.
Devart Excel Add-in for Freshdesk allows you to connect Microsoft Excel to Freshdesk, quickly and easily load data from Freshdesk to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Freshdesk. It enables you to work with Freshdesk 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.
dotConnect for FreshBooks is an ADO.NET provider for working with FreshBooks data through the standard ADO.NET or Entity Framework interfaces. It allows you to easily integrate FreshBooks data into your .NET applications, and integrate FreshBooks services with widely used data-oriented technologies. dotConnect for FreshBooks has the same standard ADO.NET classes as other standard ADO.NET providers: FreshBooksConnection, FreshBooksCommand, FreshBooksDataAdapter, FreshBooksDataReader, FreshBooksParameter, etc. This allows you quickly get started with it and eliminates the need to study any FreshBooks data access specificities.
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.
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.
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.
Devart Reviews
Anna R.
TMetric shows what my team focuses on
Justin W.
Effortless ETL Automation with Reliable Precision
Frederik I.
dbForge Studio Makes Database Compare and Data Search Easy
About
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.