13 Examples Of Useful Data Virtualisation Tools

By Indeed Editorial Team

Published 28 May 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Data management is a crucial process for most businesses with a large scale of operations. By merging information from many data sources into a single, streamlined database, data virtualisation techniques can make data collecting and analysis faster and more direct. Understanding what data virtualisation is and the technologies that enable it may help you choose the proper software for future workplaces if you are interested in working in a company's or organisation's data management department.

In this article, we define what tools for data virtualisation are and list 13 useful tools that exist in the market that enable businesses and organisations to integrate data across different platforms.

What are data virtualisation tools?

Data virtualisation tools are a type of data integration software that allows users to access real-time data on a single, simplified platform. It enables clients to access, monitor and alter data regardless of their actual location, making it a valuable asset for employees that work in a variety of settings. These tools collect data from a variety of sources and organise it so that clients may access it regardless of format, platform or source. Through its streamlined approach, data virtualisation can save businesses both time and money by circumventing the time-consuming and complex process of manual data integration.

Related: 13 Data Mining Techniques: A Complete Guide

13 useful data virtualisation tools

These are 13 tools for data virtualisation:

1. Cloud Pak for Data

Cloud Pak for Data is a well-known data virtualisation technology that provides users with a variety of data integration options. It has capabilities for traditional data collecting methods like replication and batch processing and more current approaches to data virtualisation and integration. The application employs artificial intelligence to make data available on any cloud for AI processing or analytics.

2. AtScale Virtual Data Warehouse

The AtScale Virtual Data Warehouse is a platform that connects a company's business intelligence tools, allowing employees to access and reference data without having to copy it to another platform or device. This application can make it easier for users to access data by eliminating the need for an extract, transform and load (ETL) procedure, as the tool's data abstraction engine automatically transforms data into the correct format. In addition, the AtScale Virtual Data Warehouse connects with a variety of business intelligence products, allowing users to access data in a consistent and secure manner.

3. CONNX Data Virtualization

The CONNX Data Virtualization system is a tool that combines several data sources into a single source, allowing users to simultaneously access multiple databases in real-time. This tool includes over 150 database adapters, allowing you to connect databases from all over the world. Due to its capacity to maintain data in its original form even after the user has extracted it from its primary source, the CONNX system can help limit the risk of errors or data loss.

4. TIBCO Data Virtualization

TIBCO Data Virtualization is a platform that analyses and detects data set relationships, allowing users to extract data from various data sources at once. This system also includes a transformation engine, which gathers data from several sources and combines it into a single source. One of TIBCO's most well-known features is its unique programme interface, which allows clients to select data from an extensive database.

5. Informatica-PowerCenter

Informatica-PowerCenter is a data virtualisation technology that can assist companies looking for a platform that includes data quality features. One of the most appealing aspects of this tool is that it operates without the need for specialised code, making it more accessible to those who are less familiar with technology and data collection. It also comes with a metadata manager, which provides a visual editor for organising a company's data flow into a clear map. It includes an effect analysis tool that determines the potential impact of a data integration activity on a business.

Related: Top 20 Big Data Tools: Big Data And Types Of Big Data Jobs

6. Denodo

Denodo is a data virtualisation software that enables users to convert data into a virtual format. It has a parallel processing system that can reduce network traffic and improve response times for huge data sets. Customers can also utilise the programme's catalogue feature to identify and archive their data, which they can then find using simple search queries.

7. Stone Bond Enterprise Enabler

The Enterprise Enabler from Stone Bond is a data utility that offers data virtualisation services that work with a variety of data sources. This utility tool is also compatible with cloud systems. The technology comes in three different bundles, each with different data sources, allowing customers to choose the level of data virtualisation they require.

8. Lyftron

Lyftron is a data virtualisation technology that centralises datasets and manages a single data platform to increase company productivity and employee accessibility. The application allows users to mine data in real-time without needing to first analyse the data format or type. It is cloud-based data storage compatible, and it integrates the most prominent public cloud vendors on a single platform, allowing users to mine data from a variety of sources.

9. Red Hat JBoss Data Virtualization

The Red Hat JBoss Data Virtualization system is a data virtualisation platform that is suitable for businesses that value programming and developer input. The application, like other data virtualisation solutions, integrates data from multiple sources into a single, streamlined source, eliminating the need to identify where the data originates from. It also creates a virtual database that is compatible with most standard interfaces and a unique data grid where users can easily access data using a simple search.

10. Big Data SQL

Big Data SQL allows you to access data from Oracle's Database, Hadoop and a variety of other sources with a single query. SQL users and applications have access to a significantly larger data set. A business can use SQL's full capabilities to evaluate all their data volumes together. Users can utilise the tried-and-tested Smart Scan scale-out processing feature to get rapid query results.

Related: What Is Big Data Hadoop? (Definition And Career Opportunities)

11. VMware vCloud Director

VMware vCloud Director (vCD) is multi-tenant cloud deployment, automation and management software for virtual infrastructure resources. Cloud service providers can use VMware vCD to transform physical data centres into highly elastic virtual data centres (VDCs). It accomplishes this by transforming actual data centre resources like network, storage and computation into virtual data centre resources, which the service provider then makes available to internal customers as catalogue-based services through a web portal. VCD includes policy controls that allow users to set pre-determined limitations on their resource consumption and access.

The organisation is one of the important concepts in VMware vCD. The vCD administrator creates an organisation, which is a collection of users and groups. The vCD admin creates an organisation and assigns resources to it, which it receives from the VDC. In addition, The VDC provides an environment in which you can store, deploy or operate on virtual systems. More than one VDC can provide resources to an organisation. A single organisation can also have an unlimited number of users and groups.

12. SAP HANA

SAP HANA is a high-performance analytics platform based on a SAP-developed in-memory columnar database. SAP HANA stores data in memory (RAM), giving CPUs instant access to data for processing. With Haswell-based processors, it can handle about 3 billion scans per second per core and 20 million aggregations per core per second.

SAP HANA supports the source computing paradigm and offers a number of methods for moving application functionality into the database. Because SAP HANA is a columnar database, it only scans the desired table columns and moves selection constraints or filters on table columns to the table level, allowing you to access and aggregate only the requested rows, resulting in a significant reduction in data transfer to the application layer. At the database level, SAP HANA also provides a specific library layer for advanced analytics like text, geo-spatial, predictive, machine learning and graph analysis.

13. AWS glue

AWS Glue is a fully managed ETL (extract, transform and load) service that enables categorising, cleaning and enriching, and makes reliably moving data across various data storage and data streams simple and cost-effective. AWS Glue is made up of three parts: the AWS Glue Data Catalog, an ETL engine that creates Python or Scala code automatically and a customisable scheduler that manages dependency resolution, task monitoring and retries.

Please note that none of the companies, institutions or organisations mentioned in this article are associated with Indeed.

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