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Devart SSIS Data Flow Components for Jira allow you to integrate Jira data with other databases and cloud applications via SQL Server Integration Services (SSIS). They include optimized Jira Source, Jira Destination, and Jira Lookup components and provide their own Jira Connection Manager with lots of Jira-specific connectivity features. - Export data from Jira to various sources - Import XML, CSV, and other files to Jira - Automate Jira integration via SSIS Data Flow tasks - Migrate from/to Jira using SSIS - Synchronize Jira with SQL Server or other data sources - Integrate various data sources with Jira via SSIS
The PostgreSQL Python Connector by Devart is a reliable and efficient solution designed to facilitate seamless interaction between Python applications and PostgreSQL database servers. Fully implementing the Python DB API 2.0 specification, this connector enables developers to perform create, read, update, and delete operations on PostgreSQL databases without the need for additional client libraries. 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: - Direct Connection: Establishes a direct TCP/IP connection to PostgreSQL servers, eliminating the need for database client libraries and enhancing data transmission speed. - High Performance: Supports batch processing of multiple update statements, improving execution times and overall application performance. - Fast Deployment: Simplifies deployment across multiple user workstations by removing the requirement for distributing database client libraries. - Secure Communication: Ensures data security through support for SSL/TLS encryption, SSH tunneling, and HTTP/HTTPS tunneling between the Python application and PostgreSQL server. - 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: Offers extensive support for all PostgreSQL and Python data types, with customizable options for data type mapping. Primary Value and User Benefits: The PostgreSQL Python Connector addresses the need for a robust and straightforward method to connect Python applications with PostgreSQL databases. By providing a direct connection, it enhances data transmission speeds and simplifies deployment processes, especially in environments requiring distribution across multiple workstations. Its support for secure communication protocols ensures data integrity and security, while compatibility across major operating systems and comprehensive data type support make it a versatile tool for developers. Ultimately, this connector streamlines database interactions, allowing developers to focus on building efficient and secure applications.
The Oracle Python Connector by Devart is a robust and efficient solution designed to facilitate seamless interaction between Python applications and Oracle database servers, including managed database services. Fully implementing the Python DB API 2.0 specification, this connector enables developers to perform create, read, update, and delete operations on stored data without the need for Oracle Client installations. 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 Oracle databases, eliminating the need for Oracle Client and 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 removing the requirement for Oracle Client installations, thanks to its direct connection capability. - Secure Communication: Ensures encrypted communication between Python applications and Oracle servers using SSL/TLS, SSH tunneling, and HTTP/HTTPS tunneling. - Platform Support: Compatible with Windows , macOS , and Linux . - 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 Oracle and Python data types, offering options to control data type mapping between the two. Primary Value and User Solutions: The Oracle Python Connector addresses the need for a reliable, high-performance, and secure method to connect Python applications with Oracle databases. By enabling direct connections without the necessity for Oracle Client installations, it streamlines deployment processes and reduces setup complexities. Its support for encrypted communications ensures data security, while compatibility across multiple platforms and Python versions enhances its versatility. This connector is particularly beneficial for developers seeking an efficient and straightforward solution for database operations in Python applications.
dotConnect for Zoho Books is an ADO.NET provider for working with Zoho Books data through the standard ADO.NET or Entity Framework interfaces. It allows you to easily incorporate Zoho Books data into your .NET applications, and integrate Zoho Books services with widely used data-oriented technologies. dotConnect for Zoho Books has the same standard ADO.NET classes as other standard ADO.NET providers: ZohoBooksConnection, ZohoBooksCommand, ZohoBooksDataAdapter, ZohoBooksDataReader, ZohoBooksParameter, etc. This allows you to quickly get started and eliminates the need to learn any specific details of accessing Zoho Books data. - Direct access to the Zoho Books data - High performance - Comprehensive security features - Broad compatibility with .NET platforms - Visual Studio integration
dotConnect for Zoho Desk is an ADO.NET provider for working with Zoho Desk data through the standard ADO.NET or Entity Framework interfaces. It allows you to easily incorporate Zoho Desk data into your .NET applications, and integrate Zoho Desk services with widely used data-oriented technologies. dotConnect for Zoho Desk has the same standard ADO.NET classes as other standard ADO.NET providers: ZohoDeskConnection, ZohoDeskCommand, ZohoDeskDataAdapter, ZohoDeskDataReader, ZohoDeskParameter, etc. This allows you to quickly get started and eliminates the need to learn any specific details of accessing Zoho Desk data. - Direct access to the Zoho Desk data - High performance - Comprehensive security features - Broad compatibility with .NET platforms - Visual Studio integration
dotConnect for Dynamics 365 (formerly Dynamics CRM) is a high-end ADO.NET data provider for accessing and managing Dynamics 365 data through the standard ADO.NET or Entity Framework interfaces. It helps you easily integrate Dynamics 365 data into .NET applications. Our data provider has the same standard ADO.NET classes as other providers. This helps you get started quickly and eliminates the need to study any specifics of Dynamics 365. - Broad compatibility with .NET platforms, including WPF, Blazor, MAUI, Windows Forms, 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
The MongoDB Python Connector by Devart is a robust solution designed to facilitate seamless interaction between Python applications and MongoDB databases. Fully implementing the Python DB API 2.0 specification, this connector allows developers to perform create, read, update, and delete operations on MongoDB 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 enables batch processing of multiple update statements, enhancing execution times and overall application efficiency. - Secure Communication: It supports SSL/TLS encryption, ensuring secure data transmission between the Python application and the MongoDB server. - Platform Support: Compatible with Windows , macOS , and Linux , the connector caters to diverse development environments. - Data Types Support: The connector supports all MongoDB and Python data types, offering additional options to control data type mapping between the MongoDB data types and Python data types. Primary Value and Problem Solved: The MongoDB Python Connector addresses the challenge of integrating Python applications with MongoDB databases by providing a reliable and efficient connectivity solution. By enabling SQL-like interactions with MongoDB data, it simplifies database operations for developers accustomed to relational database management systems. Its support for secure communication and high performance ensures that applications can handle data operations swiftly and safely, thereby enhancing overall productivity and data integrity.
Devart Excel Add-in for Marketo allows you to connect Microsoft Excel to Marketo, quickly and easily load data from Marketo to Excel, instantly refresh data in an Excel workbook from the database, edit these data, and save them back to Marketo. It enables you to work with Marketo 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 SSIS Data Flow Components for DB2 allow you to integrate DB2 data with other databases and cloud applications via SQL Server Integration Services (SSIS). They include optimized DB2 Source, DB2 Destination, and DB2 Lookup components and provide their own DB2 Connection Manager with lots of DB2-specific connectivity features. - Export data from DB2 to various sources - Import XML, CSV, and other files to DB2 - Automate DB2 integration via SSIS Data Flow tasks - Migrate from/to DB2 using SSIS - Synchronize DB2 with SQL Server or other data sources - Integrate various data sources with DB2 via SSIS
Devart Reviews
Sophiia Z.
Does the job without much maintenance
Zsolt C.
Full SQL Freedom for DDL and DML—A Reliable Tool for Years
Sophiia Z.
Time Tracking That Keeps Marketing Work Organized
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.