Monitoring and keeping track of big data from multiple sources is a task that companies often can’t do with traditional data processing software. Data virtualization tools can make data collection and analysis a significantly faster and more direct process by combining information from multiple data sources into a single, streamlined database. If you’re interested in working as part of a company or organization’s data management department, understanding what data virtualization tools can be helpful for choosing the right software for future workplaces.
In this article, we define what data virtualization is and list nine data virtualization tools on the market.
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What is data virtualization?
Data virtualization is an approach to integrating data that gives users real-time data access on a single, streamlined platform. It allows customers to access, monitor, and make changes to data no matter their physical location, which makes it a helpful asset for employees who conduct business in a variety of work environments.
It pulls information from multiple data sources and centralizes it so that users can access data regardless of its format, platform, or source. Data virtualization can save businesses both time and money through its streamlined approach by bypassing the time-consuming and intricate process of manual data integration.
Data virtualization tools
Here are nine data virtualization tools on the market:
1. IBM Cloud Pak for Data
IBM Cloud Pak for Data is a popular data virtualization platform that offers its users several distinct tools that aim to improve productivity and reduce complexity. Its features include tools for traditional data collection methods, such as replication and batch processing, and a more modern approach to integration and data virtualization. The program uses artificial intelligence to make data accessible for AI purposes or analytics on any cloud.
2. IBM Virtual Data Pipeline
Virtual Data Pipeline powered by Actifo provides copy data management for various workloads either on-premises or in hybrid or multi-cloud environments. The product integrates seamlessly with existing toolchains and allows for self-service. It allows employees to turn data silos into data pipelines by recovering data across any cloud from any point in time. It also offers a range of security tools that help to protect and secure the data no matter where it is stored.
3. CData Software
CData Software offers solutions for real-time access to databases, on-premises applications, online applications or Web APIs. It provides access through various established application platforms, offering a good level of security and assurance. Its products are available in six categories, including enterprise connectors, data visualization, driver technologies, ETL and ELT solutions, OEM and custom drivers, and API connectivity.
4. CONNX data access and virtualization
The CONNX data access and virtualization system is a tool that integrates data sources into a single source, allowing users to access multiple databases at once in real time. The tool offers over 150 database adapters to connect databases across a large spectrum. The CONNX system can help reduce the risk of errors or data loss due to its ability to keep data in its original form even after the user has extracted it from its primary source.
5. TIBCO Data Virtualization
TIBCO Data Virtualization is a platform that analyzes and identifies relationships between data sets, giving users the ability to extract data from multiple data sources at a time. The system also includes a transformation engine that takes data from different sources and joins them into a single source. One of TIBCO’s most popular attributes is its unique program interface, offering an expanding portfolio of integration tools and a self-service directory of virtualized data.
6. Informatica’s PowerCenter
Informatica’s PowerCenter is a data virtualization tool aimed at organizations searching for a program that integrates data quality tools as part of its platform. One of the key features of this tool is that it uses a code-free system that makes it more accessible for individuals less versed in technology and data collection. It also includes a metadata manager, which helps users by providing a visual editor that organizes a company’s data flow into a concise map.
It offers an impact analysis tool that identifies the potential impact a data integration effort can have on a company. Informatica also has a range of other data management software products, with strong interoperability between products.
7. Denodo
Denodo is a data virtualization tool that offers data integration, data management and data delivery, transforming data into a visual format. It has a parallel processing system that can minimize network traffic and subsequently increase the response time for running large amounts of data. The program also has a catalog feature that gives customers the ability to identify and archive their data, which they can find in the future with the use of a search query.
8. Stone Bond Enterprise Enabler
Stone Bond’s Enterprise Enabler is a data tool that provides data virtualization services that are compatible with various data sources, including cloud systems. The tool is highly scalable, unifying information silos across multiple data sources in real time.
It’s available in three bundles with varying data surreal-timing its user’s flexibility when deciding on the scale of data virtualization they want and need. While the headquarters are located in the United States, it offers services to European and South American countries, making it a more widely accessible platform for data virtualization.
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9. Red Hat Developer JBoss Data Virtualization
The Red Hat Developer JBoss Data Virtualization system is a data virtualization tool most compatible with organizations that prioritize programming and developer input. The tool sits in front of multiple data sources, allowing teams to use multiple sources like a single source and extract data when they need it. It also creates a virtual database that is compatible with most standard interfaces and even provides a unique data grid where users can quickly access data with a short search.
Pros and cons of data virtualization tools
These are some potential benefits and disadvantages of data virtualization tools:
Pros
These are some pros of data virtualization tools:
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Real-time access: These tools allow you to access the original source of the data without physically relocating the new location.
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Improved security: Businesses can centralize data governance to enhance data security using these tools.
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Cost-effective: Using data virtualization requires fewer resources and doesn’t require data consolidation using new systems, which can save money.
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Self-service capability: It doesn’t matter where the data is stored or the format, employees can access the data they need when they need it.
Cons
These are some potential drawbacks of data virtualization tools:
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Single failure point: If the server goes down, employees risk losing their data feeds when using data virtualization tools.
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Time spent locating results: It can take a lot of time to prepare test environments, especially when the team works with large volumes of data.
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Batch processing conflicts: Large batch processes on large databases can potentially lead to conflict with other teams.
I hope you find this article helpful.
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