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Data Virtuality Platform

Score8 out of 10

1 Reviews and Ratings

What is Data Virtuality Platform?

The Data Virtuality Platform is a data integration and management solution designed to integrate data from various sources, regardless of type, format, or location. According to the vendor, this platform targets small to large enterprises and is suitable for data architects, data engineers, business analysts, heads of data, and DevOps professionals. It finds applications across industries such as e-commerce/retail and financial services, offering a unified data access layer and streamlining data integration processes.

Key Features

Connect: According to the vendor, the platform enables the integration of data from disparate sources using methods like data virtualization, ETL/ELT, streaming, and CDC.

Query: The platform allows users to create a central data logic using SQL language for data queries, simplifying data integration and enabling the retrieval of specific information from multiple sources.

Replicate: The platform seamlessly replicates data using SQL commands translated into native data source commands, supporting real-time replication from various sources into a centralized data repository.

Deliver: According to the vendor, the platform facilitates the delivery of data to any data consumer, supporting integration with a wide range of tools and applications, and providing flexibility in delivering data in various formats and programming languages.

Data Governance: The platform offers robust data governance features, including data quality controls, access controls, and compliance with data regulations and standards, to ensure data integrity, security, and compliance.

Business Data Shop: The platform provides a centralized data marketplace for users to discover and access pre-integrated data sources, streamlining the data discovery and access process while promoting collaboration and knowledge sharing.

Security, Authentication, Audit: According to the vendor, the platform implements security measures, authentication mechanisms, and auditing capabilities to protect data, control access, and ensure compliance with data security and privacy regulations.

Change Data Capture (CDC): The platform captures and replicates only changed data in real-time, supporting incremental updates and enabling efficient and timely data replication for near-real-time analytics and reporting.

Optimization: The platform optimizes data integration and query performance through query optimization techniques, caching mechanisms, and tools to enhance the overall data integration workflow, according to the vendor.

Streaming: According to the vendor, the platform supports real-time data streaming, enabling the integration of streaming data sources into the data integration pipeline and facilitating the processing and transformation of streaming data in real-time.

“Integration of data is quick, strong, and centralized.”

Use Cases and Deployment Scope

We use Data Virtuality, a fantastic concept that simplifies

mapping data structures to relational tables. It's brilliant to use a few lines

of SQL to connect to SFTP Server, query new JSON files, convert them to XML,

and map all acquired data to the relational model for the warehouse. About 20

lines of clean, well-structured SQL code are needed. There are pipes in place

for each potential data source. Pipes was the only option we found that met our

requirements, as it was both reasonably priced and included an integrated SQL

editor, making ETL a breeze. I like data replication and stored procedures

language (more than T-SQL)—customer support is excellent. If there's a bug,

they fix it quickly and send us the patch. Thus, I have a fair opinion of the

Data Virtuality Platform.

Pros

  • ETL/ELT model building is flexible.
  • The pipes' setup and use are intuitive.
  • It lets us access various data sources, extract, and analyze data.

Cons

  • Configuring data connectors can be tricky.
  • Price could be more flexible and adapt to the use case.
  • The ETL builder's user interface could be prettier.

Most Important Features

  • Data accessibility.
  • Rapid prototypes of BI.
  • Centralized business logic data.
  • Stored procedure data flow automation.

Return on Investment

  • It has the capability of integrating data from a variety of different sources.
  • It improved development and user interface to offer a robust MDM repository and strategy.
  • It offers a comprehensive solution for processing and retrieving data, which is one of the ways it assists.

Alternatives Considered

Qlik Replicate

Other Software Used

Denodo, SAP HANA Cloud, Tableau Desktop, Adobe Illustrator CC, Keap