Overview
Product Information on CData Virtuality
What is CData Virtuality?
CData Virtuality Pricing
Overall experience with CData Virtuality
“DV: An excellent tool for data integration”
About Company
Company Description
CData Software provides data integration and connectivity solutions that enable access to data from a wide range of on-premises and cloud-based applications. Designed to support diverse deployment environments—including on-premises, cloud, and hybrid—CData solutions simplify how users connect, integrate, and work with data. By facilitating easy and secure data access across systems, CData helps organizations accelerate decision-making, improve process efficiency, and advance data-driven initiatives.
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Reviewer Insights for: CData Virtuality
CData Virtuality Likes & Dislikes
It is a robust data federation tool that offers a seamless unified layer to access and process data from a multiple data sources all in a single interface. Its user-friendly environment enables users to easily query databases from various vendors, APIs, and flat files all using SQL. This significantly improves your data integration and processing tasks in terms of performance and maintainability. In addition, the functionalities to have a complete automated data processing pipeline is very impressive. Users can intuitively create and schedule jobs that can access tables, views, and stored procedures from numerous data sources and perform complex processing tasks periodically with minimal effort. Query optimizer tool is also very effective in enhancing performance that makes retrieval and processing more efficient.
The studio tool enables very efficient data exploration and agile development. The scheduler is straightforward without limitations and its GUI makes it easy to analyze performance and schedule appropriately.
Easy to use, easy to learn
Python Coding feature is an exciting addition to their toolbox that can improve your experience considerably. However, the lack of access to some of the most widely used external Python libraries such as Pandas and Numpy is a bit limiting to perform more complex data processing tasks. Having access to those libraries will reduce the need to transfer data between multiple development environments, which will enhance both the experience and performance. In addition, although most of the existing utility functions in DV are very practical, there are a few areas where revisions could be considered mainly for performance reasons. For example, upserting data into tables takes longer using the related utility function in comparison to what you would experience by executing standard SQL commands in Postgres. Although it is not a major issue for smaller datasets, for relatively larger datasets or more complex tasks, it should not be neglected.
Hoping to see improvements to the Studio UI such as viewing an existing schedule in a more easily readable way, and the ability to edit a schedule, rather than deleting it and recreating.
Web Interface Handling should be improved on some sides (e.g. sorting of lists should be possible)
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Peer Discussions
CData Virtuality Reviews and Ratings
- Data Engineer50M-1B USDHealthcare and BiotechReview Source
DV: An excellent tool for data integration
Overall, DV is a perfect tool for data integration and process automation. With the addition of support for external Python libraries and some minor improvements in performance, it will be an even more powerful tool for your complex data processing tasks. - DATA ENGINEER50M-1B USDHealthcare and BiotechReview Source
Fantastic product
DV is a joy to use, allowing us to concentrate on the data with seamless federation through connections to anything we throw at it. - IT Senior Business Analyst50M-1B USDBankingReview Source
Very good product!
For the first time it is possible to combine data from different sources without manual work like 'export to excel, manipulate, deliver it somewhere else' - Data Analyst50M-1B USDHealthcare and BiotechReview Source
DV - A modern platform to meet all of your BI requirements.
Data Virtuality provides an easy to use and flexible tool that covers a lot of BI-related use cases. As a Data Analyst I use Data Virtuality on a daily basis, for example to create automated business reports, to build views for Tableau or for ad-hoc analysis. The tool provides a great framework to access multiple data sources through a virtualization layer. As a user I don't need to understand the specifics of every source system, I only need to know how to write standard SQL, the universal language of Data Virtuality. The Data Virtuality company also has an excellent customer support team which is always available to provide solutions if we ask for help. - Data and Analytics Manager<50M USDMediaReview Source
A powerful data virtualisation and ETL tool
We're using Data Virtuality to access our customer's data to create self-service analysis both internally and for client stakeholders. It's key to our data integration and ETL/ELT processes, offering real-time data access when needed.