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Top Data Virtualization Tools

Thursday December 1, 2022. 12:33 AM , from eWeek
Data virtualization is the process of cleansing and integrating data from various sources so it can be more readily accessed and analyzed by business users. It eliminates redundancy, standardizes formats, and makes data accessible through a single source. It integrates business intelligence, data visualization, and databases to help users query and analyze data while keeping them secure.

What are Data Virtualization Tools
Best Data Virtualization Tools
SAP HANA Cloud
Denodo
TIBCO Data Virtualization
Oracle Virtualization
Red Hat jBoss Data Virtualization
Actifio GO
AtScale
IBM Cloud Pak for Data
Informatica PowerCenter
Stone Bond Enterprise Enabler
SAS Federation Server
K2View Dynamic Data Virtualization
Cdata
Data Virtuality
Key Feature of Data Virtualization Solutions
Benefits of Data Virtualization Software
Choosing the Best Data Virtulization Tool for Your Enterprise

What are Data Virtualization Tools
Data virtualization tools are used to uncover data insights using a combination of data discovery, data modeling, and virtual data integration. They provide access to information without requiring detailed knowledge of its source or structure.
Data virtualization tools simplify data integration processes using metadata to understand each data source’s structure, semantics, and usage. A data virtualization solution bridges the gap between isolated systems. It enables users with self-service capabilities to access various data sets from multiple sources within or outside an organization.
Also see: Best Data Analytics Tools 
Best Data Virtualization Tools
Many companies are looking for the best data virtualization tools to work with as they explore ways to increase their productivity and efficiency. To help them make an informed decision, we have compiled a list of the top data virtualization tools rated highly by experts and users.
These rankings were based on popularity, ease of use, and how much value each data virtualization tool provides its users. Implementing one of these technologies can reduce operational costs and improve data quality.
Also see: Top Data Visualization Tools 
SAP HANA Cloud

SAP HANA Cloud is a single database as a service (DBaaS) foundation for modern applications and analytics across all enterprise data. It’s a comprehensive, scalable and flexible in-memory database – with an elastic, on-demand pricing model that allows organizations to pay only for what they need. It also offers advanced data virtualization capabilities – Including data federation, integration and replication – to move data seamlessly among different sources and formats so users can query any data type or source without concern for underlying schema complexity.
With SAP HANA Cloud, customers can build modern applications that combine data from many sources and run them at scale without compromise. Customers can leverage big data capabilities like distributed processing and real-time event handling to create a new generation of apps that support today’s analytics, collaboration, machine learning and digital transformation needs.
Key features

Data, federation integration and replication.
Provides comprehensive business visibility with a real-time gateway to all your data across apps, data storage, multi-cloud, and hybrid environments.
This tool is capable of handling OLTP and OLAP workloads for a variety of transactional and analytical databases.
Perform commands, and automate and customize applications.
Predict IT upgrades’ performance and cost-effectiveness and secure your IT landscape during and after changes.
Configure, modify, and monitor database performance, and automate advanced processes.
Stores, processes, and analyzes geospatial, graph, JSON document, and other data.

Pros

Friendly user interface.
Integration with other SAP products.
Saves maintenance cost.
Feature-rich.

Denodo

Denodo is a leading data integration, management and delivery platform that helps enterprises manage their entire data infrastructure. It offers the widest range of capabilities for accessing, handling and delivering all types of data across clouds, databases and Big Data environments without moving it from its original repositories.
It also delivers a single version of truth for analytics across all sources and governance to ensure compliance with company standards. Denodo is built for both technical and business users, including CIOs, CDOs, CDAOs, enterprise architects, developers, data scientists, and cloud architects.
Key features

Denodo Platform can be licensed on AWS Cloud, Microsoft Azure, and Google Cloud Platform for faster deployment.
Connects to any data source, including databases, data warehouses, cloud applications, big data repositories, and Excel files.
Denodo is built to integrate, manage, and deliver data in complex, hybrid, multi-cloud systems while maintaining high performance, security, and governance.
Denodo platform enables self-service BI, data science, hybrid/multi-cloud data integration, and corporate data services.
Combine data from various sources, including structured, streaming, social, and flat files

Pros

Consolidate data from multiple sources.
User friendly.

TIBCO Data Virtualization

The TIBCO Data Virtualization solution delivers a complete, self-service data virtualization environment for business intelligence (BI), data warehousing and analytics. With the solution, users can consolidate all their enterprise data sources into one virtualized platform and easily build and manage new data connections to systems they need to access.
TIBCO data virtualization empowers IT departments by consolidating existing disparate toolsets so they can focus on managing how business information is accessed and used across the organization. It gives analysts immediate access to all data, which helps them develop actionable insights and act on them in real-time. Using a self-service directory of virtualized business data, users can search, select, and use BI or analytics tool to get results.
Key features

Its web UI is a self-service data provisioning and data catalog web user interface that lets users browse for accessible data and develop and publish their views for usage in third-party applications.
Integrated governance and security ensure the delivery of only sanctioned data, including visibility, traceability, provenance, control, authentication, authorization, and encryption.
Developers use the graphical modeling environment to model data, design data services, implement transformations, optimize searches, and manage resources.
Its centralized metadata management enables users to create and show detailed entity relationship diagrams and data models to meet new business needs.
Its advanced query engines let users query, federate, abstract, and deliver data.

Pros

Connects to multiple databases.
Fast data query.
Easy to use with minimal technical support.

Oracle Virtualization

Oracle Virtualization is a flexible and easy-to-use tool that can be used with various platforms. It also includes high availability, load balancing, and virtual machine management. Built for security, efficiency and performance, Oracle Virtualization provides exceptional reliability. In addition, it’s an easily customizable platform that allows for smooth scalability and large data volumes.
Key features

Supports on-premise and cloud workload.
Enable security updates without rebooting.
Patches hypervisors automatically with zero downtime.

Pros

Easy to manage
Integration with other Oracle solutions

Red Hat jBoss Data Virtualization

Red Hat jBoss Data Virtualization enables enterprises to work more efficiently by providing data abstraction, federation, integration and transformation capabilities. It helps organizations reduce costs of development and deployment with the ability to combine data from one or multiple sources into reusable logical data models.
With JDBC (Java Database Connectivity) or ODBC (Open Database Connectivity) access, organizations can access the information with their existing applications. A rich set of web services APIs enables cross-platform connectivity to third-party systems, including other enterprise databases, NoSQL databases, SaaS, and flat files for agile data utilization.
Key features

Offers centralized access control, and auditing.
Simplifies data access to speed application development and integration.
Offers read/write access to heterogeneous data storage in real-time.
Integrate and transform data semantics per user needs.

Pros

Highly scalable and flexible.
Ease of use.
Comprehensive documentation.
Efficient support team.

Actifio GO

Actifio GO is a data management platform that provides organizations with automated, self-service provisioning and refresh of enterprise workloads. Actifio enables enterprises to stay current with rapidly evolving IT needs while safeguarding their business-critical data and ensuring regulatory compliance. Additionally, Actifio integrates with Google Cloud Storage (GCS) via its Nearline storage service for backup and disaster recovery for GCP or hybrid environments.
Key features

Data encryption in transit and at rest.
Multi-region disaster recovery.
Self-service sign-up, simple deployment and central management for backup and recovery of VMs, SQL Server and SAP HANA databases inside Google Cloud and on-premises VMware VMs.
SLA-driven data management.

Pros

Data recovery.
Efficient customer support.
Multi-region disaster recovery.
Access data instantly, even after unsubscribing.

AtScale

AtScale is an enterprise-grade data virtualization platform that enables organizations to securely and rapidly access data from various sources. The semantic layer solution leverages the robust infrastructure of cloud data platforms such as Snowflake, Databricks, Microsoft Azure, Amazon Redshift and Google BigQuery to provide end-to-end support for analytics. It provides a platform for integration, analytics acceleration and orchestration of these engines via its Semantic Layer.
The tool allows data consumers to seamlessly connect with the analytics tools they already use, like Tableau, PowerBI, Excel, Jupyter and Looker. Companies can have their organization’s complete portfolio of business intelligence (BI) tools in one place while managing all data dependencies.
Key features

Data integration, blending and migration.
AtScale’s Insights models and workbooks provide multidimensional Cloud OLAP analysis without data prep or engineering.
Its virtual cube catalog enables easy, frictionless access to vast data.
Its design canvas visually and intuitively connects to any data.

Pros

SQL Server Analysis Services (SSAS) performance improvement.
Efficient support team.

Also see: Top Data Mining Tools 
IBM Cloud Pak for Data

IBM CloudPak for Data is a data and AI platform that delivers on-demand insights to business leaders. It provides instant access to all your company’s data and lets you run predictive analytics. IBM CloudPak for Data offers various deployment options, including an on-premises software version built on the Red Hat OpenShift container platform or a fully managed version built on the IBM Cloud.
The tool manages data spread across distributed stores and clouds by providing an intuitive user interface that makes all of it easily accessible. IBM CloudPak for Data also integrates with other IBM products to provide end-to-end data management and security features.
Key features

Utilize Netezza, a high-performance data warehouse, to enhance analytics.
Prepare, cleanse, and govern your data in the same tool.
End-to-end AI lifecycle.
Deliver a unified experience based on metadata and active policy management.

Pros

Intuitive user interface.
Multi-cloud storage option.
Feature-rich.

Informatica PowerCenter

Informatica PowerCenter is a leading enterprise-class data integration platform that enables you to integrate and transform data to accelerate business insight. It provides out-of-the-box capabilities for unstructured data, enterprise applications, cloud and SaaS applications, predictive analytics and machine learning. PowerCenter supports analytics and data warehousing, application migration, consolidation, and data governance.
Key features

Users may use data transformation to parse JSON, PDF, XML, Microsoft Office, and IoT for non-relation data.
The product offers tools for analytics, data warehousing, data governance, consolidation, and application migration.
Cloud applications connectivity.
Rapid prototyping, profiling, and validation.
Script-free automated data validation testing.

Pros

Maintains data quality during the ingestion and integration process.
Supports public clouds such as Microsoft Azure and Amazon Web Services.
Automation.
Collaboration.

Stone Bond Enterprise Enabler

Stone Bond Enterprise Enabler is a data and application integration that delivers a set of enterprise-ready components to create and deliver high-quality business information. It integrates data virtualization, extract, transform, load (ETL), enterprise application integration (EAI), service-oriented architecture (SOA) and master data services in a single platform.
It facilitates the delivery of valuable insights from disparate sources of information for decision-making purposes. Integrating data from heterogeneous databases into one uniform presentation with metadata about the underlying structure enables easy access to data for collaboration and visualization purposes.
Key features

Simple drag-and-drop to auto-generate virtual models in minutes or seconds for BI reports, web services, and apps.
Automatically develop and host queryable virtual models (ODBC, JDBC, SOAP, REST, oData, ADO.Net, and BDC or BCS).
Data masking and obfuscation.
Consolidate all EE features, including Enterprise Enabler Studio, self-service portal, web APIs, and documentation in one console.

Pros

Supports GDPR compliance, RLS, and CLS.
Data lineage.

SAS Federation Server

SAS Federation Server data virtualization software provides a business-centric view of all enterprise data, empowering organizations to find, use, and deliver the information they need to make better decisions.
With SAS Federation Server, you can centralize disparate data sources within your organization’s infrastructure, simplify connections to remote locations, and securely share access to the appropriate data sources with those who have been granted access permissions. The result is an easier-to-use environment that optimizes user productivity while reducing administration costs and complexity.
Key features

Improved performance with in-memory data caches and scheduling.
Defines a user or group’s catalog, schema, table, column, and row access permissions.
Apply data quality functions such as match-code generation, parsing and other tasks inside the view.
Advanced data masking and encryption.
SAS Federation Server accesses, manages, and shares SAS data with major relational databases such as DB2, Oracle, SAP, SQL Server, Teradata, and Greenplum.

Pros

Ease of use.
Interactive interface.
Improves efficiency.

K2View Dynamic Data Virtualization

K2View is a leading data virtualization software company. Their dynamic data virtualization platform ingests data from various sources. It unifies, transforms, and enriches it to be shared across users and systems to enable more insightful decision-making. K2View’s solution for data virtualization also handles data masking tools when required, ensuring the privacy of sensitive information throughout the process.
Key features

Enables access to live data through a logical abstraction layer.
The tool allows you to choose which data product data will be virtualized, unified, processed, orchestrated, and delivered from source to destination.
Implement reverse ETL.
Compliant with data privacy regulations such as GDPR, CCPA/CPRA, LGPD, HIPAA, and PCI DSS.

Pros

Centralized data management.
Integration on-prem, in the cloud, or hybrid.
High-scale data delivery.

Cdata

Cdata is a data connectivity and integration tool that offers customers a flexible approach to handling, transforming, and integrating large sets of diverse data sources. It can connect to various data sources, including cloud and SaaS applications, data warehousing, management, governance, AI, ML, BI and analytics and other enterprise application systems.
The solution integrates data from multiple systems and formats into a centralized repository where business users can leverage it, analytic models and advanced processes at both the transactional and deep insights levels.
Key features

Cdata drivers, adapters, and cloud connectivity solutions provide real-time data to Tableau, Power BI, Excel, Sisense QuickSight, DataStudio, and Spotfire.
Enterprise-level ETL may bring together the information stored in any large database or data warehouse so that it can be accessed whenever necessary by users, including analysts, data scientists, developers, AI, and decision-makers.
Cdata offers visual and secure application and data integration solutions based on an open architecture.

Pros

Easy to implement.
Supports multiple databases.
Automatically and continuously integrate data into Google BigQuery, Snowflake, Microsoft SQL Server, and Amazon Redshift.

Data Virtuality

Data Virtuality is a scalable data virtualization platform that combines data virtualization and ETL to provide data professionals with a data integration tool that enables them to extract any data from their legacy systems, transform it into a format suitable for use in modern applications, and distribute it across their environment. The tool offers self-service interfaces for business users and developers who need data connectivity without the involvement of IT experts.
Key features

Agile data management.
Offers over 200 data connectors.
Use metadata repositories to improve master data management.

Pros

Self-service capabilities.
Supports several use cases, including data governance, data quality checks, self-service BI, and data preparation.
Flexible ETL/ELT model building.

Also see: Top Cloud Companies
Key Features of Data Virtualization Solutions
There are several features to consider when shopping for a data virtualization tool. They include:
Fully integrated
Data virtualization solutions integrate the data and processes of all aspects of your organization – from master data management to business intelligence. This means that information is always current, accurate, and seamlessly accessible across the enterprise.
Comprehensive
A data virtualization solution provides a single point for accessing all data types, including transactional, analytic and structured/unstructured data sources. The ability to query by either metadata or content makes it easy to access just the suitable dataset without performing complex searches through multiple databases.
Centralized deployment of rules
Different departments within an organization may have different views on how data should be organized, processed and accessed. Data virtualization software gives you central control over these decisions so organizations can take advantage of data no matter where it resides in its raw form.
Business users don’t need training in specific programming languages; they can create custom data models, views, queries and reports with drag-and-drop simplicity. The fact that there is one version of the truth for all team members removes potential disagreements over data definitions and opportunities to work around IT rules by sending inquiries directly to individual databases.
Access controls
Data virtualization software offers flexible security options for controlling who has access to data. It also provides role-based controls (such as access privileges based on roles) to give users only the rights they require to perform their job functions.
Zero latency
Most data virtualization solutions offer zero latency querying, even when combining datasets stored in disparate systems. Allowing interactive, ad hoc exploration and analysis of datasets as they are being loaded dramatically reduces query timeframes and frees up scarce IT resources for other projects.
Easily consistent
Data virtualization software keeps creating, distributing and maintaining master data consistent and error-free because it supports integration between corporate applications such as CRM, ERP and OLAP tools.
Data transformation
With data transformation, you can quickly and automatically convert your data into the format required by any downstream system. This eliminates the need to manually reformat data whenever you want to use it in a different system.
Multidimensional analysis
Data virtualization software enables this analysis, which involves examining multiple perspectives on a set of data simultaneously. This allows analysts to explore and analyze trends and relationships in ways that would not otherwise be possible. As part of this capability, data virtualization also stores subsets of data from each dimension, allowing them to be combined and analyzed.
Also see: Real Time Data Management Trends
Benefits of Data Virtualization Software
Data virtualization software offers several benefits that can help companies improve their data management and analysis. This includes easily accessing data from all sources, which is often difficult or impossible in the absence of data virtualization software.
It also provides an environment where different data types can be analyzed and queried relatively easily and simplifies storing, managing and accessing this information.
Data virtualization solutions can also eliminate many time-consuming tasks associated with maintaining complex databases and spreadsheets by centralizing disparate datasets. These features, combined with other benefits like mobility and scalability, make data virtualization software an invaluable asset for any company looking to simplify its processes.
This enables businesses to make better decisions by accessing more accurate and complete information. Other benefits include:

Ability to generate reports faster as the process does not require the same manual intervention as with traditional technologies.
Improve decision-making processes by merging disparate datasets.
It allows companies to meet compliance requirements for data reporting across organizational units or jurisdictions.
Flexible enough to adapt as new hardware or software becomes available.

Choosing the Right Data Virtualization Tool for your Enterprise
There are different types of data virtualization tools available, but not all tools are created equal.
Choosing the right data virtualization tool depends on understanding how much flexibility is required by your company’s business practices; however, there are some general guidelines to follow when shopping around for this type of solution.

Make sure that any data virtualization software can work with other critical enterprise applications such as ERP or CRM.
Choose a provider that offers multiple access levels to ensure everyone has the appropriate level for their job function.
Make sure you’re getting value for money because it can get expensive quickly when deploying large amounts of technology across an organization.
Be sure to check out customer reviews before making any final decisions. These reviews can help determine whether the product is worth the cost.
Find out about training and support options offered by each vendor before buying.
Ensure that training is included in the package price and that you’ll have 24/7 access to support staff after purchase. It’s also helpful if vendors provide templates or plug-ins that make it easier for new users to use the data virtualization tool without having extensive technical knowledge.

Finding the perfect data virtualization software for your enterprise can be challenging with so many factors involved. However, considering these five features can go a long way toward finding success in the data virtualization sector.
The post Top Data Virtualization Tools appeared first on eWEEK.
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