Data virtualization offers access to information while encapsulating technical aspects, such as location, access language, or structure. With this particular technology, applications can gain access to data without knowing where it’s being kept. Data virtualization is primarily implemented in data federation, making data in different data storages function in such a manner that the consuming application can treat it as one single data storage.
In sharp contrast with ETL (extract, transform, and load) technologies, data virtualization tools are capable of providing responses to queries in real-time while the information stays in place and remains safeguarded from being replicated. Furthermore, they require fewer resources and happen to be increasingly responsive when compared to their ETL peers.
Top Five Data Virtualization Tools for 2021 and Beyond
Denodo continues to be amongst the most popular data virtualization tools for businesses seeking to visualize their data and gain extensive insights on what data they manage. Denodo’s latest iteration comes with a nifty data catalog utility that allows the end-users not just to virtualize and group information but to identify and catalog it as well.
The data catalog option in the seventh version of Denodo allows users to do a semantic search for finding information and extract valuable insights on how other applications and users are making use of it. It’s also equipped with query optimization and parallel processing to minimize network load and can also prove to be useful in reducing response times when working with large data sets.
The Cloud Pak for Data offered by IBM can be particularly beneficial for companies that intend to employ a converged solution for managing the tedious task of data accumulation and analysis. It was previously branded as Cloud Private for Data and was renamed in 2018.
The Cloud Pak for Data is a unified ecosystem that allows businesses to gather as well as analyze information by using the same platform. The key logic for workflow organization is based on the given project, with advanced user controls for data governance and accessibility for every action.
The Informatica PowerCenter is no doubt an excellent alternative for companies that require a top data virtualization tool with integrated features for data quality validation. It’s widely acknowledged as one of the selected few data integration tools for its rich arsenal of powerful utilities.
Its greatest USP lies in the ease of use. PowerCenter is known to provide users with a graphical-user-interface-based environment that requires no coding for integrating virtually any kind of data. One of the key attributes of PowerCenter is its metadata manager that not only does a great job of integrating data but also offers a visual editor that the users can make good use of in generating data flow maps across an environment.
Businesses that already have other applications in place from Oracle, one of the key players when it comes to offering data virtualization services, its Data Service Integrator can turn out to be an easy and obvious choice for creating data visualizations.
One of its most unique features is the capability to read and write data from several sources, which allows this data virtualization tool to be immensely useful in a myriad of use-cases. As the graphical modeling feature is responsible for service integration in the Data Service Integrator, users are not required to explicitly code the integration
The JBoss Data Virtualization from Red Hat can be an extremely favorable choice for development-centric organizations and for anyone who uses containers as well as microservices for creating and activating a virtual data barrier to isolate information sources that are disparate.
The abstraction layer created by this data virtualization tool can function similar to a virtual database that can be accessed and used through a standard interface. It offers an Eclipse-Integrated-Developer-Environment-based graphical user interface, enabling the developers to leverage their existing knowledge and current toolsets.
So, here’s our list of some of the most popular data virtualization tools that are worth trying in 2021. Let us know in the comment section which one among them your organization utilizes and why, or are planning to buy?