Data Virtualization Tools

TrustRadius Top Rated for 2023

Top Rated Products

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1
IBM Cloud Pak for Data

IBM Cloud Pak for Data (formerly IBM Cloud Private for Data) provides data management, data governance, and automated data discovery and classification.

2
SAP HANA Cloud

SAP HANA is an application that uses in-memory database technology to process very large amounts of real-time data from relational databases, both SAP and non-SAP, in a very short time. The in-memory computing engine allows HANA to process data stored in RAM as opposed to reading…

3
TIBCO Data Virtualization

TIBCO Data Virtualization is an enterprise data virtualization solution that orchestrates access to multiple and varied data sources and delivers the datasets and IT-curated data services foundation for nearly any solution.

All Products

(1-25 of 211)

1
SAP HANA Cloud

SAP HANA is an application that uses in-memory database technology to process very large amounts of real-time data from relational databases, both SAP and non-SAP, in a very short time. The in-memory computing engine allows HANA to process data stored in RAM as opposed to reading…

2
TIBCO Data Virtualization

TIBCO Data Virtualization is an enterprise data virtualization solution that orchestrates access to multiple and varied data sources and delivers the datasets and IT-curated data services foundation for nearly any solution.

3
Informatica PowerCenter

Informatica PowerCenter is a metadata driven data integration technology designed to form the foundation for data integration initiatives, including analytics and data warehousing, application migration, or consolidation and data governance.

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4
IBM Cloud Pak for Data

IBM Cloud Pak for Data (formerly IBM Cloud Private for Data) provides data management, data governance, and automated data discovery and classification.

5
Delphix

Delphix, headquartered in Redwood City, provides test data management for DevOps. Businesses need to transform application delivery but struggle to balance speed with data security and compliance. The Delphix DevOps Data Platform automates data security, while rapidly deploying test…

6
Denodo

Denodo is the eponymous data integration platform from the global company headquartered in Silicon Valley.

7
Oracle Data Service Integrator

Oracle Data Service Integrator provides companies the ability to develop and manage federated data services for accessing single views of disparate information. Oracle Data Service Integrator is standards based, declarative, and enables re-usability of data services.

8
IBM Db2 Big SQL

IBM offers Db2 Big SQL, an enterprise grade hybrid ANSI-compliant SQL on Hadoop engine, delivering massively parallel processing (MPP) and advanced data query. Big SQL offers a single database connection or query for disparate sources such as HDFS, RDMS, NoSQL databases, object stores…

9
Red Hat JBoss Data Virtualization

JBoss Data Virtualization is a data integration solution that sits in front of multiple data sources and allows them to be treated as a single source, to deliver the right data, in the required form, at the right time to any application and/or user. Also presented as a lean, virtual…

10
Presto

Presto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases. Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.

11
Data Virtuality Platform

Data Virtuality, headquartered in Leipzig, offers two products to solve data integration and management problems in a tailored way that best suits data teams in the fast-paced world of data. The Data Virtuality Platform combines data virtualization and data replication, Data Virtuality…

12
Informatica Cloud Data Integration

Informatica Cloud Data Integration, for Cloud ETL and ELT, enables users to ingest, integrate and cleanse data within Informatica's cloud-native ETL and ELT solution. Users can link source and target data with thousands of connectors that recognize metadata, to make it easier to…

13
IBM InfoSphere Optim

IBM InfoSphere® Optim™ solutions manage data from requirements to retirement, to improve governance across applications, databases and platforms by managing data properly, enabling organizations to support business goals with less risk.

14
Azure SQL Managed Instance

Azure SQL Managed Instance is a scalable cloud database service that combines SQL Server database engine compatibility with a fully managed and evergreen platform as a service.

15
Oracle Big Data SQL Cloud Service

The Oracle Big Data Cloud Service is a PaaS supporting data scientists with secured and encrypted Hadoop clusters, running a diverse set of workloads from Hadoop-only workloads (ETL, Spark, Hive etc.) to interactive, all-encompassing interactive SQL queries using SQLon-Hadoop tools…

16
Starburst Enterprise

Starburst Enterprise is a fully supported, production-tested and enterprise-grade distribution of open source Trino (formerly Presto® SQL). It aims to improve performance and security while making it easy to deploy, connect, and manage a Trino environment. Through connecting to any…

17
DATPROF Subset

With DATPROF Subset users can extract specific selections out of production databases and make them directly available within the test environment.

18
MOSTLY AI
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MOSTLY AI offers synthetic data for use cases ranging from AI and machine learning development to generating realistic test data. The platform boasts many database connections and features to automate data generation pipelines.

19
Keenlog Analytics

Keenlog Analytics provides intelligence to the SMB business and supports decision-makers with the necessary data visibility to control and take actions to meet their logistics’ financial and market goals. The vendor states the product includes the following: • More…

20
ChaosSearch
0 reviews

ChaosSearch, in Boston, is a log analytics solution aims to provide enterprises with data lakes that turn cloud object storage into analytics engines. ChaosSearch features a stateless architecture that separates storage from compute, and data is stored in Amazon S3. It is accessible…

21
Stone Bond Enterprise Enabler

Enterprise Enabler is a data virtualization or data integration platform from Stone Bond Technologies in Houston, Texas.

Learn More About Data Virtualization Tools

What are Data Virtualization Tools?

Data Virtualization Tools simplify and expedite access to data stored in data warehouses, databases, and files located on-premises and in the cloud. By connecting multiple data sources and centralizing data acquisition logic in a metadata layer, these tools create a single source of data for data consumers. The tools support real-time and historical data. They’re compatible with a wide range of formats and interfaces and facilitate data modifications and updates.

Data virtualization tools decouple data consumers from the data acquisition logic. This allows business intelligence (BI) tools and a variety of other applications and services to acquire data from the same metadata layer. By creating a single data source, data virtualization expands BI capabilities and streamlines the development and maintenance of apps and web services. The data these tools provide supports analytics, machine learning, artificial intelligence, and application development.

Data virtualization tools can connect data from sources like relational databases, data warehouses, data lakes, other apps, cloud data, web services, IoT data, XML files, and Excel spreadsheets. Data virtualization tools also integrate with a variety of enterprise data applications, such as Amazon Redshift, Google Big Query, Microsoft SQL, IBM DB2, Oracle, and Teradata.

Data virtualization is heavily utilized by the financial services, energy, technology, communications, and manufacturing industries and by government and healthcare agencies.

The tools are used by data architects and engineers, database administrators, developers, and business users. The latest trends for data virtualization include edge data IoT integration, regulations regarding data movement and security, and cloud data sharing.

Data Virtualization vs Data Integration

Data virtualization tools and data integration tools have significant overlap. The key difference is that data virtualization tools do not move or copy data. Instead, they create a standardized virtual interface that connects to the original data. When the original data changes, the virtual interface reflects those changes without needing to run extract, transform, and load (ETL) processes.

Data Virtualization Tools Features

Data virtualization tools commonly include the following features:

  • Connect to multiple data sources
  • Support for on-premises, cloud, and hybrid data sources
  • Support for different data types
  • Abstraction of the technical characteristics of data, such as API, query language, structure, and location
  • Centralize data acquisition logic in a virtualized metadata layer
  • Real-time data retrieval, delivery, and updates
  • Data federation, integration, and transformation for data consumers
  • Query optimization
  • Data modeling and profiling
  • API management
  • Support for JDBC, ODBC, REST interfaces
  • Advanced caching
  • Admin dashboards including connection and cache monitoring
  • Permission management
  • Workflow management
  • Quality management
  • Data governance
  • On-premises or cloud installation

Data Virtualization Tools Comparison

Consider the following when purchasing data virtualization tools.

Integrations: Since the entire purpose of data virtualization is to connect disparate data into a single source, proper integration is all-important. Ensure that your data virtualization tools will work with the systems you already have in place.

Performance: Data virtualization can add overhead that may impact query performance. Make sure to choose a data virtualization product with query monitoring and optimization tools.

Security: Your organization’s data security policies may be impacted by implementing data virtualization. Many solutions have ways to address these concerns, but it’s important to ensure that you choose a tool with the right data security features for your organization.

Scope of virtualization: Data virtualization tools are great for integrating multiple data sources. However, virtualizing and centralizing all of an organization’s data can create new problems. For instance, accessing operational data that is crucial to mission-critical production systems has the potential to impact their performance and integrity. Avoid deploying data virtualization tools for more data sources than necessary.

Pricing Information

Data virtualization tools don’t advertise their pricing, so you will need to contact a vendor for a quote. The scale of your virtualization needs, number of sources, amount of data, and number of queries supported all factor into subscription-based pricing. Free trials are commonly available.

Data Virtualization Tools Best Of Awards

The following Data Virtualization Tools offer award-winning customer relationships, feature sets, and value for price. Learn more about our Best Of Awards methodology here.

Best Data Virtualization Tools

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Frequently Asked Questions

What do data virtualization tools do?

Data virtualization tools connect multiple data sources, centralize data retrieval logic, transform data, and deliver data to data consumers. By creating a single view of data, these tools facilitate data access for BI tools, applications, and web services.

What are the benefits of using data virtualization tools?

By eliminating the need for data consumers to know the location or configuration of data, data virtualization tools reduce complexity, minimize data redundancy, help enforce consistency, streamline application development and maintenance, and lower costs. Their flexibility facilitates faster business intelligence gathering, analytics, and reporting.

What are the best data virtualization tools?

Popular data virtualization tools include: