The 24 Best Data Virtualization Software for Winning Data Strategies of 2024
10 Best Data Virtualization Software Shortlist
Here's my pick of the 10 best software from the 24 tools reviewed.
Our one-on-one guidance will help you find the perfect fit.
Data is the lifeblood of modern business, but extracting meaningful insights from disparate sources remains a major challenge. Traditional integration methods struggle with performance, agility, and governance.
Data virtualization offers a solution by creating a unified view across systems—eliminating silos, improving access, and speeding up insights. But with so many options, choosing the right software is no easy task.
This guide breaks down the top data virtualization solutions to help you easily navigate on-premises, cloud, and hybrid data environments.
Need expert help selecting the right tool?
With one-on-one help, we guide you to your top software options. Narrow down your software search & make a confident choice.
What is Data Virtualization Software?
Data Virtualization Software is a practical data management tool adopted primarily by businesses, analysts, and IT professionals. This type of software creates an integrated view of data from diverse, disparate sources, such as databases, ODBC (Open Database Connectivity), JDBC (Java Database Connectivity, analytic and structured/unstructured data sources, applications, and systems, enabling users to access, manipulate, and interpret this data without knowing its physical location or format.
Data virtualization software can bridge the gap between different forms of data, be it relational or unstructured. This innovative approach offers real-time access and on-demand provisioning, surpassing traditional data integration tools.
By forming an integrated data layer, data virtualization technology streamlines your workload, making it more efficient and cost-effective. It leverages machine learning business intelligence, supports caching, and can access data from various sources, including web services and open-source platforms. It effectively solves the pain points associated with fragmented datasets and warehousing.
Best Data Virtualization Software Summary
| Tools | Price | |
|---|---|---|
| OneHub | From $20/user/month | Website |
| CData Driver Technologies | From $99/user/month (billed annually) | Website |
| Denodo Platform | Pricing upon request | Website |
| Ansarada | Pricing upon request | Website |
| Cisco Data Virtualization | Pricing upon request | Website |
| TIBCO Data Virtualization | Pricing upon request | Website |
| Datasite Diligence Virtual Data Room | Pricing upon request | Website |
| SAP HANA | Pricing upon request | Website |
| Dremio | From $20/user/month (billed annually) | Website |
| Firmex | Pricing upon request | Website |
Compare Software Specs Side by Side
Use our comparison chart to review and evaluate software specs side-by-side.
Compare SoftwareBest Data Virtualization Software Reviews
Onehub is a powerful tool to facilitate secure file sharing and online collaboration. The software offers full features that make it ideal for businesses aiming to streamline their document collaboration and file-sharing processes, justifying its tag as 'Best for robust online file sharing and collaboration.”
Why I Picked Onehub:
I picked Onehub for this list because of its comprehensive features tailored for online collaboration and secure file sharing. It stands out from other tools due to its custom branding abilities and detailed permission settings that ensure file security. This makes it the best tool for robust online file sharing and collaboration.
Standout Features and Integrations:
Onehub provides secure file sharing, virtual data rooms, and client portals. It has intuitive features like drag-and-drop file uploads and Google Docs integration, making collaboration easier.
It integrates with various platforms, including Google Workspace, Office 365, and API for custom integrations, thus fitting well into existing workflows.
Pros and cons
Pros:
- Seamless integration with Google Workspace and Office 365
- Detailed permission settings for file security
- Custom branding options for personalized file sharing
Cons:
- Additional cost for extra users
- The user interface could be more intuitive.
- Pricing might be high for small businesses.
Best for connecting applications, databases, and APIs in real-time
CData Driver Technologies is a connectivity solution aimed at simplifying the way businesses connect with data across various applications, databases, and APIs. This tool stands out for its prowess in offering real-time connectivity, which justifies it as the go-to tool for real-time application, database, and API connections.
Why I Picked CData Driver Technologies:
I picked CData Driver Technologies for its capability to provide real-time connections across diverse data landscapes. Its universal data connectivity, combined with its easy-to-use driver technologies, set it apart from other tools. Given its strength in connecting applications, databases, and APIs in real-time, it is clear why it fits the bill for this specific use case.
Standout Features and Integrations:
CData Driver Technologies provide a range of essential features such as SQL-92 compliant querying, full CRUD (Create, Read, Update, Delete) support, and real-time data synchronization.
The platform integrates with numerous popular databases, applications, and APIs, including SQL Server, MySQL, Salesforce, and Google Analytics, to name a few, making it highly versatile for diverse business needs.
Pros and cons
Pros:
- SQL-92 compliant querying and full CRUD support
- Universal data connectivity, able to integrate with many databases, applications, and APIs
- Exceptional at offering real-time connectivity across applications, databases, and APIs
Cons:
- Complex queries may require manual optimization.
- It may present a steep learning curve for non-technical users.
- High starting prices might be prohibitive for small businesses.
Denodo Platform is a data virtualization solution that provides data abstraction across various sources. It is particularly effective in delivering enterprise-wide data management, making it an excellent choice for businesses looking for a holistic approach to handling their data.
Why I Picked Denodo Platform:
I chose the Denodo Platform because of its advanced data abstraction capabilities and broad scope of data delivery. It differs from other tools because of its comprehensive, enterprise-wide data management, a feature not many platforms offer. Considering these factors, I judged that Denodo is ideally suited for businesses needing a wide-reaching, adequate data abstraction and delivery tool.
Standout Features and Integrations:
Denodo Platform includes data cataloging, data governance, and real-time data access. It provides an inclusive view of the data, delivering a more comprehensive perspective to users.
The platform integrates seamlessly with popular enterprise platforms like Oracle, SAP, and Microsoft SQL Server. These integrations are essential for businesses that use these platforms and want to get the most out of their data.
Pros and cons
Pros:
- Provides real-time data access, which can be crucial for making immediate business decisions
- Ability to integrate with popular enterprise platforms like Oracle, SAP, and Microsoft SQL Server
- Comprehensive data abstraction and delivery for enterprise-wide data management
Cons:
- The platform could be complex for smaller businesses or those with more straightforward data needs.
- It may require technical expertise for the effective utilization of its features.
- Pricing information is not readily available, which might cause uncertainty in budget planning.
Ansarada is a platform designed to facilitate merger and acquisition (M&A) processes and manage critical business events efficiently. Ansarada can simplify complex transactions and ease navigation through essential business situations by offering a highly structured environment. This reinforces its standing as the optimal tool for M&A deals and critical business events.
Why I Picked Ansarada:
Ansarada was an easy pick for my list due to its unique focus on M&A processes and critical business events, a niche few other platforms target as effectively. I was particularly impressed by how Ansarada structures data to make complex transactions more digestible. Its emphasis on streamlining M&A deals and essential business events drove me to label it the best in this category.
Standout Features and Integrations:
Ansarada stands out with its highly structured data rooms that make managing due diligence during M&A transactions easy. The platform also features AI-powered insights that can guide strategic decisions. On the integration front, Ansarada smoothly interfaces with Salesforce, boosting its utility by linking CRM data with due diligence processes.
Pros and cons
Pros:
- Useful integration with Salesforce
- Provides a structured environment for complex transactions
- Focused tool for managing M&A processes and critical business events
Cons:
- Not as flexible for non-M&A related use cases
- It might be overkill for smaller companies.
- Pricing information not readily available
Best for integrating multi-vendor, multi-platform data sources
Cisco Data Virtualization is a powerful tool businesses can use to integrate data from various vendors and platforms. It consolidates large volumes of data from different sources, transforming them into meaningful, actionable information, making it an ideal choice for complex data integration tasks.
Why I Picked Cisco Data Virtualization:
I selected Cisco Data Virtualization because it exhibits a strong capability for handling diverse and complex data integrations. The tool's unique function of abstracting data from multiple sources without needing physical data movement sets it apart from its competitors. It is the 'Best for integrating multi-vendor, multi-platform data sources.”
Standout Features and Integrations:
Cisco Data Virtualization offers data federation, transformation, and delivery capabilities. Its high-speed query engine enables real-time data access and decision-making. Another noteworthy feature is the tool's ability to provide a unified view of data across multiple sources.
Cisco Data Virtualization integrates well with various data sources, including traditional databases, cloud applications, and Big Data solutions. This ensures seamless data gathering and processing.
Pros and cons
Pros:
- High compatibility with various data sources, including cloud and Big Data solutions
- Real-time data access for faster decision-making
- Provides a unified view of data from multiple sources
Cons:
- Relatively high learning curve compared to some other data virtualization tools
- It could be complex for beginners to set up and use
- Pricing information is not transparently disclosed.
TIBCO Data Virtualization is a comprehensive data integration solution that simplifies access to complex data sources. It is especially well-suited for organizations dealing with multifaceted data environments, hence why it's considered 'best for handling complex data environments with agility.'
Why I Picked TIBCO Data Virtualization:
In choosing tools for this list, I was particularly impressed by TIBCO Data Virtualization's capacity for dealing with complex data landscapes. It stands apart due to its robust capabilities, including data federation, transformation, and delivery to meet users' needs. Its adaptability and advanced functionality make it the top pick for handling complex data environments with agility.
Standout Features and Integrations:
TIBCO Data Virtualization's key features include data abstraction, which simplifies complex data structures, and data federation, allowing it to integrate data from multiple sources without physically moving it.
The software integrates well with a broad range of data sources, including traditional databases, cloud-based data, and big data solutions, which makes it versatile in handling diverse data environments.
Pros and cons
Pros:
- Integrates well with various types of data sources
- Provides comprehensive data integration features such as data federation and transformation
- Exceptional capabilities in managing complex data landscapes
Cons:
- Requires substantial resources for optimal performance
- The platform may be complex to use for beginners.
- Pricing is not transparent, requiring direct contact for a quote.
Best for conducting fast and safe due diligence
Datasite Diligence Virtual Data Room is a comprehensive platform that simplifies and secures due diligence processes. Its features focus on speed and security, which are crucial for conducting due diligence, making it the 'best for conducting fast and safe due diligence.”
Why I Picked Datasite Diligence Virtual Data Room:
I chose Datasite Diligence Virtual Data Room for this list because of its unique focus on due diligence procedures. Its standout feature is the ability to streamline these processes in a highly secure environment, differentiating it from other platforms. Therefore, it truly is the best tool for conducting fast and safe due diligence.
Standout Features and Integrations:
Datasite Diligence Virtual Data Room offers several notable features, including artificial intelligence to automate document sorting and redaction, real-time analytics, and advanced search capabilities for efficient navigation.
The platform integrates well with various data providers and CRM systems, facilitating import/export and enhancing the due diligence process.
Pros and cons
Pros:
- Integrations with various data providers and CRM systems
- Real-time analytics to monitor user activity
- Advanced artificial intelligence capabilities for document management
Cons:
- It might be overly complex for small-scale due diligence processes.
- The learning curve may be steep for some users.
- Pricing information is not readily available.
SAP HANA is a high-performance in-memory database that accelerates data-driven, real-time decision-making and actions. Its proficiency in handling large volumes of data and executing transactions and analytics on a single platform is why it's ideal for leveraging in-memory data processing capabilities.
Why I Picked SAP HANA:
SAP HANA was an easy choice for this list due to its unique in-memory data processing capability. It outshines others with its high-speed performance and ability to manage transactional and analytical data on a single platform. These attributes make SAP HANA the prime tool for capitalizing on in-memory data processing capabilities.
Standout Features and Integrations:
Key features of SAP HANA include real-time data analytics, predictive analytics, and spatial processing, which allows organizations to process and analyze large volumes of data quickly.
The platform provides a variety of integration options. It pairs effectively with other SAP offerings, third-party solutions, and data sources, ensuring your business processes are streamlined and efficient.
Pros and cons
Pros:
- A wide array of integration possibilities
- Capability to handle both transactional and analytical data on a single platform
- Highly efficient in-memory data processing
Cons:
- Requires substantial resources and skills to implement effectively
- The platform may need to be more complex for smaller businesses.
- Transparent pricing information is not publicly available.
Dremio is a data lake engine designed to simplify and expedite the process of accessing and analyzing your business data. It bridges the gap between your data storage and consumers, aligning perfectly with its prowess in accelerating analytics on any data source.
Why I Picked Dremio:
I selected Dremio primarily for its ability to perform lightning-fast queries on your data, irrespective of the source, making it a powerhouse for analytics acceleration. Its capability to curate all data into a more manageable, high-performing, and reliable state sets it apart from the crowd. My conviction that Dremio is best for speeding up analytics is rooted in its efficient architecture that breaks down data barriers, enabling faster, more accurate data analysis.
Standout Features and Integrations:
Dremio impresses with its powerful features, including a self-service semantic layer that empowers business users and a robust optimizer for lightning-fast query execution. Its collaborative interface stands out, facilitating user sharing of data and insights. As for integrations, Dremio seamlessly hooks into popular data science and BI tools like Tableau, Power BI, and Python, extending its functionality and ensuring compatibility with your existing toolset.
Pros and cons
Pros:
- Intuitive and collaborative user interface
- The powerful query optimization engine
- Robust connectivity to a multitude of data sources
Cons:
- Customization options could be more extensive
- Setup and configuration might require technical expertise.
- The learning curve can be steep for non-technical users.
Firmex is a tool built to handle owing diligence with aplomb, offering an ideal platform for managing complex, large-scale due diligence processes. It provides a high level of control, making it the go-to solution for businesses needing superior data management during extensive audits.
Why I Picked Firmex:
Firmex earned its spot on my list because of its impressive capacity to manage complicated due diligence tasks. Its ability to handle a high volume of data efficiently and safely sets it apart from its competitors. My choice of Firmex as best for large-scale due diligence processes stems from its in-depth feature set, designed to simplify and streamline extensive audits and data reviews.
Standout Features and Integrations:
Firmex boasts robust document management features that allow for meticulous organization and categorization, ensuring you always have a handle on your data. Additionally, its granular permission settings provide an extra layer of control. Regarding integrations, Firmex can work seamlessly with Microsoft Office and various cloud storage platforms, allowing for accessible data import and export.
Pros and cons
Pros:
- Valuable integrations with commonly used platforms
- High level of data control
- Specialized in due diligence operations
Cons:
- Limited flexibility in data visualization
- It may be overly complex for smaller operations.
- The need for transparent pricing could be off-putting.
Other Data Virtualization Software
Below is a list of additional data virtualization software that I shortlisted but did not make it to the top 10. Worth checking them out.
- Data Virtuality
Best for connecting all your data sources into one logical data lake
- Ideals Virtual Data Room
Best for secure document sharing and collaboration
- Eccenca Corporate Memory
Good for creating knowledge graphs for better data comprehension
- AtScale
Good for creating a single view of complex data
- K2View Data Product Platform
Good for managing data as a strategic asset
- Magnitude
Good for automating and streamlining data access
- IBM BigInsights for Apache Hadoop
Good for large-scale data processing with Hadoop
- SecureDocs Data Room
Good for facilitating due diligence in mergers and acquisitions
- Stratio Augmented Data Fabric
Good for integrating multiple data types across various sources
- Informatica
Good for enterprise data management and data integration
- Oracle Big Data SQL Cloud Service
Good for combining data across Oracle Database, Hadoop, and NoSQL
- Digify
Good for secure document sharing and tracking
- Caplinked
Good for secure file sharing and virtual data room needs
- Expero
Good for creating custom software solutions with complex data
Selection Criteria for Choosing Data Virtualization Software
While researching and trying out numerous data management and integration tools, I've learned that selecting the right one involves evaluating them against critical criteria crucial for success in this field. As a part of my evaluation process, I've tested these tools, and my selections are the ones that perform excellently in each of these criteria.
Core Functionality
- Data Integration: The tool should enable effortlessly merging and synchronizing data from various sources.
- Data Cleaning: Capabilities to identify and rectify inaccuracies, inconsistencies, and redundancies in data are crucial.
- Data Analysis: The ability to transform raw data into meaningful insights is vital.
Key Features
- Real-time Processing: Immediate data processing and updating allow timely decisions and reactions.
- Scalability: The tool should be capable of handling growing volumes of data with ease.
- Security: Robust data encryption and security measures to protect sensitive data from breaches.
Usability
- Intuitive User Interface: The tool should have a clear and intuitive interface, helping users to navigate and operate the device without requiring advanced technical skills.
- Easy Integration: The tool should easily integrate with existing systems and applications in the infrastructure.
- Quality Customer Support: Reliable and timely customer support is essential for troubleshooting issues and facilitating a smooth usage experience.
- Clear Documentation: Well-organized, thorough documentation or a learning library is essential for onboarding users and solving problems.
- Configurable Access: Especially for enterprise solutions, the tool must provide an easy way to configure role-based access, granting different permissions to other users.
Most Common Questions Regarding Data Virtualization Software (FAQs)
What are the benefits of using data virtualization software?
Data virtualization software offers several benefits. It simplifies data management by providing a unified, real-time view of data across different sources. This reduces the need for physical data movement and consolidation, leading to cost savings. It allows faster insight access as data is processed and analyzed in real time. Moreover, the software promotes better data governance, as all data can be managed and monitored from one place. Lastly, it enhances security and compliance by providing mechanisms to control data access and ensuring that data handling meets regulatory standards.
How much do data virtualization tools cost?
The pricing of data virtualization tools can vary greatly depending on their capabilities, the size of the organization, and the volume of data handled.
What are the typical pricing models for these tools?
Some standard pricing models include per-user/per-month subscriptions, annual subscriptions, and pricing based on data volume. Some providers offer a base package with the option to purchase additional features or services as add-ons.
What is the typical range of pricing for data virtualization software?
A primary data virtualization tool could start as low as $20 per user per month. Mid-range options can fall between $50 and $100 per monthly user. More comprehensive, enterprise-level solutions could cost several hundred dollars per user monthly.
What are some of the cheapest and most expensive software?
The cost of data virtualization software can range from free for some essential tools, like Microsoft Power BI, to several hundred dollars per month for more advanced, enterprise-grade solutions like Informatica and Denodo.
Are there any free data virtualization software options?
“Data is the lifeblood of modern business, but extracting meaningful insights from disparate sources remains a major challenge. Traditional integration methods struggle with performance, agility, and governance.
Data virtualization offers a solution by creating a unified view across systems—eliminating silos, improving access, and speeding insights. But with so many options, choosing the right software is no easy task.
This guide breaks down the top data virtualization solutions to help you navigate on-premises, cloud, and hybrid data environments with ease.”
Yes, there are free options available. For example, Microsoft Power BI offers a free version with limited features. However, paid versions are generally required for more advanced capabilities, especially for larger businesses.
Other Data Virtualization Software Related-Reviews
Takeaways
Choosing the right virtualization software can significantly streamline your data management processes, provide real-time insights, and enhance your organization's data governance and security. Every tool offers unique capabilities, so it's crucial to consider your specific needs and objectives.
Key takeaways:
- Understand Your Requirements: Define the specific needs of your business before starting your search. Consider your data volume, variety of data sources, required speed of data delivery, and security needs. This will help you shortlist the most relevant tools.
- Prioritize Usability and Support: Given the complexity of data virtualization, software with a user-friendly interface and robust customer support can significantly ease the implementation and usage process.
- Consider Pricing Models and Scalability: The cost of these tools can vary significantly. Understand the pricing model, check for hidden fees, and ensure the tool can scale with your growing business needs. Free or lower-cost tools can be a good starting point for smaller businesses or those with less complex data needs.
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Today's data-saturated landscape means effective data management is essential for business success. Data virtualization offers a powerful solution to overcome data silos and unlock valuable insights.
This comprehensive guide helps you find the right data virtualization software for your needs. Consider storage virtualization software to select the ideal platform to enhance data accessibility, improve query performance, and accelerate decision-making.
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