Data Virtualization tools provide an efficient method to interact and work with data across multiple platforms and sources, without the need for physical data storage or transportation. This method of data integration helps in reducing complexity, cutting costs, and improving the speed and overall agility of the data management process. Data virtualization allows users to gather, manage, and analyze data from various heterogeneous sources such as databases, APIs, services, and systems, all in real-time.
Data virtualization achieves this by creating an abstraction layer over complex data infrastructures, allowing it to present data in a consistent and unified manner. This approach allows businesses to view their data in a comprehensive, cohesive format instead of scattered across multiple systems. Users can work with the virtualized data directly, without knowing the intricate details of the underlying data architecture.
The market for data virtualization tools is competitive, with numerous vendors offering their services. While most options provide the same basic functionality, the competitive edge comes in the areas of capabilities like data discovery, data governance, metadata management, performance optimization and integration with business intelligence tools.
In this shortlist, we will discuss the top data virtualization tools based on their functionality, ease of use, scalability, integration capabilities, and customer feedback. The intention is to give readers an overview of the best solutions available, helping you to choose the ideal tool for your organization’s requirements.
CData provides embedded data virtualization solutions. They focus on eliminating data bottlenecks and providing a unified data access layer across various data sources. CData has recognized the fluctuating market landscape where data is split across multiple platforms; this creates data silos and slows down data transfer, potentially impacting the accuracy of business analysis.
CData’s data virtualization solution embeds a data virtualization layer into systems, thus creating a universal data access layer. CData Driver technologies enhance virtualized data connectivity and are compatible with popular data access standards such as ODBC, JDBC, ADO, and Python.
Unlike independent data virtualization solutions that can be large, costly, and difficult to manage, CData’s embedded solution can be tactically deployed as part of other applications. The company offers the CData Query Federation Driver for users who need to join data across multiple sources. This simplifies application development by allowing developers to interconnect multiple data processing systems through a single SQL-based interface. It also facilitates writing queries to combine data from different sources on-demand. CData’s solution offers improved data connectivity speeds compared to traditional data warehousing and ETL, making it up to 85% faster.
CData Virtuality, formerly Data Virtuality before it was acquired in 2024, is a data integration platform that offers real-time data access, modeling, governance, and delivery. This is achieved using data virtualization combined with varied data movement techniques such as ETL/ELT and CDC. The platform promotes direct access to over 200 sources, thereby enabling quick insights. Its data models adapt in real-time across the enterprise negating the need for ETL rebuilds.
The Data Virtuality platform offers unified security and governance with centralized controls amplifying data security, quality, and compliance. Leveraging its high-performing data engine that includes caching, query-push down, and materialization, it ensures efficient data handling of large-scale operations. The platform can be operated via SaaS, on-premises, or self-hosted cloud options, reducing total cost of ownership, and making integration straightforward.
Data Virtuality supports seamless connection to varied data sources, ensuring enterprise-wide data access. Notably, it takes a significant step forward in data integration by unifying the best elements of data virtualization and ELT/ELT into a single, broad view data management solution. This approach helps save up to 80% of cost and accelerates time-to-value by 5 times.
Through its SQL-based approach, Data Virtuality connects to multiple data sources and lets users query data from these sources efficiently. In addition to creating a central data logic that unifies the business logic and the logical connections, it also facilitates data replication to a chosen data warehouse. Finally, standard interfaces such as JDBC, ODBC, REST, OData make the data easily accessible to varied data consumers, including reporting tools, advanced analytics tools, and customized programs.
Dendo aims to provide logical data management capabilities to various organizations. Their core technology, Data Virtualization, creates a single data-access layer. This centralized access to multiple enterprise data sources, including data warehouses, data lakes, and enterprise applications’ data services and APIs. This enables real-time access to scattered, diverse data.
Data Virtualization not only reduces cost and enhances efficiency but also simplifies data integration from varied sources, unifies data security, and accelerates data delivery. Its abilities consist of logical data abstraction which represents data in an abstracted form, smart query acceleration that offers high-performance data access, and advanced semantics that simplifies data discovery. It offers universal connectivity to diverse data sources and facilitates easy sharing. It provides flexible data integration that adapts to a wide range of requirements and unifies security and governance for centralized application of policies across data and access methods.
The use of the Denodo Platform can lead to profit growth, risk reduction, time-to-value acceleration, technology optimization, and improved staff productivity. This feature-rich platform can serve a broad range of staff from Data Architects and Data Engineers to CTOs and Data Stewards by providing agile data integration and fostering quick responsiveness to fluctuating business needs. Dendo’s Data Virtualization enhances productivity and flexibility in data access, which can be instrumental in evolving data strategies and creating value.
IBM Cloud Pak for Data has a range of features and capabilities including data virtualization. This acts as a universal query engine that conducts distributed and virtualized queries across databases, data warehouses, data lakes, and streaming data. It reduces the need for extra manual alterations, data movement, or replication. Being vendor-agnostic, it plays a significant role in updating data architecture to accelerate digital transition.
IBM’s data virtualization facilitates the unification of data across all clouds, data lakes, warehouses, and databases. This empowers users to exploit all data for innovation purposes. Ensuring better outcomes, it integrates well-governed data from across a hybrid landscape. IBM Data Virtualization enables access to many diverse data sources through a data virtualization layer which to users and applications appears as a single logical data source.
IBM Data Virtualization aims to achieve speed and simplicity by improving performance through intelligent caching. It reduces the workload by querying data where it resides, thereby minimizing movement and copies. In addition, it capitalizes on ensuring queries run on high-quality, valid data with its end-to-end data governance. It provides flexibility and deployment according to necessity with virtualization capabilities as a service or on premises.
By providing a complete view of all connected data sources quickly, IBM Data Virtualization offers a comprehensive and simple data landscape. It manages all permissions in a virtual layer, adhering to privacy and regulatory requirements while still empowering data consumers to access the data they need. Through monitoring and caching recommendations, IBM Data Virtualization optimizes workloads and speeds up analysis.
Oracle Virtualization is powered by Oracle VM VirtualBox, an open-source, cross-platform virtualization software that enables multiple operating systems to coexist on a single device. This is a highly utilized tool for developers who need to quickly deliver code by testing on various operating systems, as well as IT teams striving to reduce operational costs and effectively deploy applications in a hybrid environment. This software can efficiently run on Windows, macOS, Linux, and Oracle Solaris systems, positioning it as an ideal solution for testing, developing, demonstrating, and distributing solutions across multiple platforms on a single device.
Oracle VM VirtualBox is lightweight, easy to install, and robustly powerful. This virtualization engine has a wide guest operating system platform coverage, from ultra-books to high-end servers. Notable benefits include the reduction of required desktop and server configurations, simplification of development environments, quick application development, quality assurance, testing, and automated deployments to the cloud. This tool can also extend the lifetime of existing computers and run almost any application on existing machines.
The Oracle VM VirtualBox features an impressive range of easy-to-use functionalities such as fast exporting to Oracle Cloud Infrastructure, support for Nested Virtualization, Guest Control File Manager for file transferal, and Virtual Machine Cloning Process which includes retaining the hardware UUID, MAC address policy, and disk image names. It also has the capability to support a host platform’s filesystem, multi-touch interfaces, and a rich range of networking models.
Performance-wise, Oracle VM VirtualBox uses the latest Intel and AMD hardware support for virtualization to deliver faster execution times across various guest operating systems. It offers improved 3D Graphic support, a high-performance storage I/O subsystem, built-in iSCSI initiators for virtual disks creation, remote display protocol for powerful remote graphical access, and the ability to connect external devices to guests. Adding to these features is the transparent encryption of data stored in hard disk images and disk image conversion through the VirtualBox GUI.
Red Hat JBoss Data Virtualization is a data integration tool that combines data from diverse sources, including relational databases, text files, web services, and both mainstream and “big data” data sources such as Apache Hadoop (Hive) and MongoDB. It provides a unified, virtualized view of data, hiding physical data source details from the end user. This solution allows users to focus on data analysis and manipulation, as it uses a virtual database to map physical data sources to integrated views.
Another solution from the same company, Red Hat JBoss Enterprise Application Platform (EAP), provides enterprise-grade security, performance, and scalability for Jakarta EE applications in various settings, be it on-premise, virtual, or in private, public or hybrid clouds. It offers a lightweight, flexible architecture optimized for cloud and containers, designed for performance and flexibility in contemporary application environments. Its service-driven component set enhances scale-out times and provides adaptability for applications deployed across different environments.
JBoss EAP assists productivity. It supports Jakarta EE and web-based frameworks such as Spring, Spring Web Flow, Spring WS, Spring Security, Arquillian, AngularJS, jQuery, jQuery Mobile, and Google Web Toolkit (GWT). In addition, it supports microservices development, allowing developers to use Eclipse MicroProfile APIs to build and deploy microservices-based applications. It offers enhanced APIs and supports standard microservices patterns for deployment, configuration, security, and observability.
Finally, JBoss EAP facilitates administration and maintenance. It has an improved management console interface that supports large-scale domain configurations. Its subscription model offers technical and business flexibility to avoid being locked into specific deployment environments, hardware machines, infrastructure, or levels of enterprise support.
SAP HANA Cloud is a data virtualization platform that allows businesses to access their data across various applications and organizational boundaries, delivering a comprehensive business view. The platform offers capabilities such as query federation on remote data sources, facilitating instant access to information without the need for costly data migration. It enables data integration and replication from any source, including SAP and third-party databases, ensuring real-time data availability.
The SAP HANA Cloud platform also includes a powerful multi-model engine that is capable of processing, storing, and analyzing various data types or models in a flexible database. This ensures that businesses can continually adapt their analytics as needs change, incorporating predictive modeling, time-series analysis, and other methodologies. In addition, SAP HANA Cloud allows direct access to business application data for simplified integration of essential business information.
SAP HANA Cloud further empowers developers to build AI-enabled applications that are secure, context-aware, and connected to essential business data. The platform’s integrated Machine Learning and Generative AI capabilities enable automated insights and optimized decision-making processes within app functionalities. The application creates context-aware outputs, securely connecting to business application data for real-time insights.
Finally, SAP HANA Cloud focuses on scalability and security, allowing developers to shift their focus from administration tasks to innovation. The platform features elastic scalability, supporting growth across all applications, data storage, and cloud landscapes. It ensures high availability with fully-managed database services and built-in security features, including data anonymization and encryption, to ensure business continuity and compliance.
TIBCO Data Virtualization is an innovative software solution that helps businesses to integrate data effectively and efficiently. Rather than aggregating data in a physical location, the platform facilitates the creation of a unified view by drawing data from multiple sources throughout the enterprise. This data integration solution eliminates the need for moving or copying data into a data warehouse, thereby reducing time spent finding data and increasing the time available for analysis.
This system empowers businesses to transform and deliver the necessary data to enhance revenue, decrease costs and risk, and improve compliance. Apart from data integration, it offers a modular structure supporting all phases of data virtualization including development, run-time, and management.
TIBCO Data Virtualization includes multiple modules. The Studio module serves as a modeling instrument, facilitating the creation of data services and transformations among other tasks, while the Web UI module offers a user-friendly, browser-based interface for business users. It incorporates adapters for wide-ranging data source connectivity and optimizers to enhance query performance. Additional features encompass security measures, flexible caching options, quality assurance, built-in governance, and administrative tools.
Finally, the platform includes a Monitor module, providing a real-time view of the data virtualization cluster, and an Active Cluster that works with load balancers to ensure high availability and scalability. The Discovery module allows users to examine data across various sources while the Business Directory aids in the search, categorization, and consumption of IT-curated data sets. This efficient data virtualization software enhances speed and cost-effectiveness in data integration.
Data Virtualization tools transform diverse and varied data sets into digital archives that can drive analysis and insights. By virtualizing data, your analysis teams and tools can access the information that they need, without having to worry about its source or how it is formatted. Virtualized data is easy to access, allowing you to generate insights with ease.
Where traditional data analysis and management processes are built around extract, transform, and Load (ETL) processes, data virtualization is lighter touch, making it faster and less resource intensive.
Data Virtualization can provide a range of benefits for your organization’s use case. These benefits predominantly revolve around modernizing your data processes to make them more streamlined and efficient. Some other benefits of Data Virtualization include:
Rather than transferring or moving data from its source, data virtualization tools create a unified digital copy of all data. This data layer can be accessed and searched more easily than having to trace all data back to its source.
Data Virtualization tools work by connecting data sources, with a centralized data area. This connection happens in real time, allowing for up to date insights to be generated. This later is sometimes referred to as a connection layer. One way to think about this process is as building a bridge from varied data sources (in different formats) to a single, unified area. Sources of data that are accessed during this process can include various spreadsheet files, big data systems, SaaS applications, cloud data warehouses and lakes, as well as SQL and NoSQL databases.
Once data bridges have been established, the abstraction layer will transform data to ensure that it is all in the same comprehensible and usable format. This unified area allows you to compare data in a like-for-like manner, regardless of its initial format or location. Other processes that occur during this layer include metadata management, data cataloguing, and data quality control. This ensures that the data can be accessed and used efficiently, without impacting on its quality or accuracy.
Beyond this abstraction layer is a consumption layer. This includes any of the analysis or business intelligence tools that are used to interrogate the data. IT staff can access the data, input complex queries, and generate informative and accurate results.
When selecting a Data Virtualization tool, Expert Insights recommends looking for the following features:
Alex is an experienced journalist and content editor. He researches, writes, factchecks and edits articles relating to B2B cyber security and technology solutions, working alongside software experts. Alex was awarded a First Class MA (Hons) in English and Scottish Literature by the University of Edinburgh.
Laura Iannini is an Information Security Engineer. She holds a Bachelor’s degree in Cybersecurity from the University of West Florida. Laura has experience with a variety of cybersecurity platforms and leads technical reviews of leading solutions. She conducts thorough product tests to ensure that Expert Insights’ reviews are definitive and insightful.