Use the comparison tool below to compare the top Data Virtualization software on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Accelario
$0 Free Forever Up to 10GBOpenLink Software
$42 per monthYouNeedIT
data.world
$12 per monthBureau Of Innovative Projects
Orbit Analytics
Data Virtuality
Delphix
SAP
IBM
$16,500 per monthSoftware AG
Informatica
TIBCO Software
CData Software
Amazon
Informatica
Lyftrondata
IBM
$699 per monthInformatica
Data virtualization software is a type of software that allows organizations to access data from multiple sources, regardless of the location or format. It enables organizations to integrate, analyze and manage their data in a virtual environment without having to physically move it. Data virtualization also helps reduce storage costs by eliminating the need for expensive hardware to store copies of data from multiple sources.
Data virtualization software works by creating an abstraction layer over existing physical and logical data sources such as databases, enterprise applications, files, and cloud services. This abstraction layer allows users to access all the underlying data sources through consistent interfaces such as SQL instead of having to learn different query languages for each separate source. This reduces complexity when accessing or manipulating large amounts of heterogeneous data as it allows integration across different types of systems and applications.
Data virtualization software can be used in conjunction with traditional ETL (extract-transform-load) processes to facilitate quicker time-to-value resulting from the near real-time availability of integrated data. There are many advantages associated with using this type of technology including improved resource utilization with minimal delays in timespan; increased scalability; ability to handle massive amounts of streaming big data; quick deployment; rapid change management; upscaling on demand; elimination of redundant copies and processing steps leading to reduced cost and/or risk exposure for disaster recovery plans.
As well as supporting ETL operations, modern-day solutions offer self-service analytics capabilities which allow business users to easily access information from diverse sources irrespective of any structural differences there may be between them – this includes relational databases, structured flat files and even unstructured ones stored within documents like PDFs or MS Office documents among others. By providing a single point for data integration, these solutions are able to eliminate manual intervention when consolidating information scattered across various systems – thereby significantly decreasing development timescales & cost along with greater flexibility when it comes to making sense out quickly changing business requirements & objectives.
In addition, Data Virtualization offers several security benefits due its ability to standardize secure user authentication & authorization methods while also providing an audit trail feature that logs & stores every single request made against its system over a specific duration along with details such as who initiated them & what action did they perform etc – all this makes it easier for administrators & managers alike monitor their environment’s usage & correct any wrongdoings before they get out hand if needed.
Data virtualization software is a powerful tool that makes it easier for organizations to access and manage the data they need, regardless of where that data is stored. This type of software helps companies break down silos and let them manipulate their data in ways they may not have been able to before.
One of the most important uses for data virtualization software is its ability to enable real-time insights. With this type of software, users can quickly access, combine, and analyze all their different types of data from multiple sources in just one place. As a result, businesses can better identify any trends or correlations between their different datasets which can lead to deeper understanding of their customers and operations. Businesses are able to gain competitive advantage and make faster decisions with up-to-date information when using this type of software.
Data virtualization also helps organizations reduce costs associated with storing multiple copies of the same data on different systems or in disparate locations. Data duplication across various databases can become costly over time both from an infrastructure perspective as well as from an operational standpoint as well. By leveraging data virtualization technology, organizations are able to consolidate multiple sources into one single repository while allowing application users direct access to the original source through a secure gateway connection which eliminates duplicate copies altogether and reduces overhead costs dramatically.
Another important benefit offered by this technology is enhanced security capabilities that protect sensitive corporate information from unauthorized access or misuse within an organization’s internal network ecosystem or even outside threats such as cyber criminals who might be trying to steal confidential customer records or other proprietary business intelligence assets. By unifying all underlying IT resources into a centralized platform, organizations are better equipped with an arsenal of tools at their disposal like role-based authentication models and encryption techniques capable enough for providing comprehensive protection against malicious actors attempting to breach organizational security protocols from any angle imaginable without sacrificing performance throughput speeds needed for today’s rising digital service demands industry-wide.
In summary, it cannot be ignored that there are many advantages for businesses when using data virtualization technology including enabling insight into valuable corporate information; reducing storage costs; strengthening IT security measures; improving accessibility; increasing ROI; automating deployment tasks; increasing employee productivity; offering more scalability options; revamping existing integration strategies along with many other potential benefits depending on specific company needs organizationally speaking so, in conclusion, you really cannot go wrong investing in such forward-thinking solutions when trying to stay ahead in today's ever-changing digital landscape.
The cost of data virtualization software can vary significantly depending on the specific features and complexity required by your organization. Basic virtualization solutions can start as low as a few hundred dollars for standalone users, while enterprise-level solutions with advanced analytics and scalability capabilities may cost tens of thousands of dollars or more.
Licensing fees for data virtualization software typically depend on the number of users using the system. Some companies offer per user pricing, while other vendors may offer a per server or concurrent user model. Additionally, many providers charge additional fees for support and maintenance that may be necessary to keep your system up and running smoothly.
In addition to licensing costs, businesses will also need to factor in the cost of hardware, storage, bandwidth and personnel time required to implement their data virtualization solution effectively into their workflow. Ultimately, organizations must consider all factors when budgeting for their data virtualization software needs in order to ensure they receive the right level of benefit at a price that fits within their overall budget.
Data virtualization software can integrate with many different types of software, including applications that use structured or unstructured data stored in relational databases, NoSQL databases, Hadoop systems and cloud-based services. By using data virtualization technology, disparate pieces of information from multiple sources can be unified and brought together into a single view for seamless analysis and reporting. Additionally, the data virtualization layer facilitates integration with authoring tools such as business intelligence (BI) platforms to create interactive visualizations that allow users to interactively explore data. Finally, some types of software are specifically designed to enhance the power of the data virtualization layer by allowing users to manipulate large amounts of complex datasets in real-time. Examples include high-performance analytics (HPA) solutions which provide advanced analytical capabilities for sophisticated decision-making and predictive modeling.