UM SaaS Cloud Drivers & Connectors
for Data Integration

The UM SaaS Cloud driver acts like a bridge that facilitates communication between various applications and UM SaaS Cloud, allowing the application to read data as if it were a relational database. The UM SaaS Cloud driver abstracts the complexities of UM SaaS Cloud APIs, authentication methods, and data types, making it simple for any application to connect to UM SaaS Cloud data in real-time via standard SQL queries.

Working with a UM SaaS Cloud Driver is different than connecting with UM SaaS Cloud through other means. UM SaaS Cloud API integrations require technical experience from a software developer or IT resources. Additionally, due to the constant evolution of APIs and services, once you build your integration you have to constantly maintain UM SaaS Cloud integration code moving forward.

By comparison, our UM SaaS Cloud Drivers offer codeless access to live UM SaaS Cloud data for both technical and non-technical users alike. Any user can install our drivers and begin working with live UM SaaS Cloud data from any client application. Because our drivers conform to standard data interfaces like ODBC, JDBC, ADO.NET etc. they offer a consistent, maintenance-free interface to UM SaaS Cloud data. We manage all of the complexities of UM SaaS Cloud integration within each driver and deploy updated drivers as systems evolve so your applications continue to run seamlessly.

Many organizations draw attention to their library of connectors. After all, data connectivity is a core capability needed for applications to maximize their business value. However, it is essential to understand exactly what you are getting when evaluating connectivity. Some vendors are happy to offer connectors that implement basic proof-of-concept level connectivity. These connectors may highlight the possibilities of working with UM SaaS Cloud, but often only provide a fraction of capability. Finding real value from these connectors usually requires additional IT or development resources.

Unlike these POC-quality connectors, every CData UM SaaS Cloud driver offers full-featured UM SaaS Cloud data connectivity. The CData UM SaaS Cloud drivers support extensive UM SaaS Cloud integration, providing access to all of the UM SaaS Cloud data and meta-data needed by enterprise integration or analytics projects. Each driver contains a powerful embedded SQL engine that offers applications easy and high-performance access to all UM SaaS Cloud data. In addition, our drivers offer robust authentication and security capabilities, allowing users to connect securely across a wide range of enterprise configurations. Compare drivers and connectors to read more about some of the benefits of CData's driver connectivity.

With our drivers and connectors, every data source is essentially SQL-based. The CData UM SaaS Cloud driver contains a full SQL-92 compliant engine that translates standard SQL queries into UM SaaS Cloud API calls dynamically. Queries are parsed and optimized for each data source, pushing down as much of the request to UM SaaS Cloud as possible. Any logic that can not be pushed to UM SaaS Cloud is handled transparently client-side by the driver/connector engine. Ultimately, this means that UM SaaS Cloud looks and acts exactly like a database to any client application or tool. Users can integrate live UM SaaS Cloud connectivity with ANY software solution that can talk to a standard database.

Using the CData UM SaaS Cloud drivers and connectors, UM SaaS Cloud can be easily integrated with almost any application. Any software or technology that can integrate with a database or connect with standards-based drivers like ODBC, JDBC, ADO.NET, etc., can use our drivers for live UM SaaS Cloud data connectivity. Explore some of the more popular UM SaaS Cloud data integrations online.

UM SaaS Cloud Analytics is universally supported for BI and data science. In addition, CData provides native client connectors for popular analytics applications like Power BI, Tableau, and Excel that simplify UM SaaS Cloud data integration. Additionally, native Python connectors are widely available for data science and data engineering projects that integrate seamlessly with popular tools like Pandas, SQLAlchemy, Dash, and Petl.