Dynamic Data Virtualization Tools

K2view data virtualization tools simplify data access and integration, from a wide range of underlying data sources, formats, and technologies.

Live data is accessed through a logical abstraction layer whose schema includes all relevant tables for a business entity (customer, product, loan, etc.).
Distributed queries are executed against the data sources, regardless of their technologies, with sub-second response time.
The logical layer serves as a common language between data producers and consumers, facilitating intuitive access to enterprise data.

With K2view Dynamic Data Virtualization tools, data teams decide which data will be virtualized and which will be persisted in a Micro-Database™ along the way. This is an advantage when you must:

Control tradeoffs between query performance and data freshness.
Minimize the load on your source systems.
Enrich your source data.
Apply Reverse ETL to update your source systems with insights from your analytical workloads.
Log changes made to an entity, to analyze it over time.

K2view enables authorized data consumers with real-time access to the data they need, without requiring an understanding of the underlying data sources.

Adapters are provided to all relational and non-relational DBs and file systems.
Data can be queried ("pulled") via APIs or JDBC, or delivered ("pushed") via data streaming or messaging methods.
Dynamic data virtualization tools assure unmatched high-speed, high-scale data delivery, from sources to targets.
By combining in-memory caching and business entity data consolidation, K2view achieves sub-second response times even for very complex queries that span multiple disparate sources.

K2view makes data virtualization quick to implement with AI-assisted setup that turns fragmented source data into governed, reusable, entity-based data products for secure, real-time access across APIs, JDBC, streaming, and messaging.

AI models entities faster by recommending the entity root and building the logical schema from source metadata, SQL queries, keys, and data patterns.
AU strengthens semantic access by generating descriptions, classifications, confidence scores, and relationship context for governed self-service consumption.
AI optimizes delivery choices by deciding which data to virtualize live and which to persist in Micro-Databases for freshness, performance, and source-load control.

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Data Virtualization tools

Dynamic Data Virtualization

Go beyond traditional data virtualization by selecting what, where, when, and how to virtualize.

A logical, semantic layer over your data sources

Democratize enterprise data access

Enterprise data integration and delivery, simplified

Automate end-to-end test data workflows across your applications

Easy access to data via business entities

Data abstraction removes complexities

Built-in Data processing, enrichment, and auditing

Dynamic data virtualization

Pull or push data access

Access any data in any method

IMPLEMENT WITH AGILITY

Quick and easy setup

Dynamic Data Virtualization for Data Products

Choose what to virtualize, cache, or store, table by table

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Beyond traditional data virtualization

QKS Group SPARK Matrix™ | Enterprise Data Fabric, Q3 2026

K2view named a Leader in Enterprise Data Fabric

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The complete handbook of data virtualization

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The patented technology of the K2view Data Product Platform

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Data Products 101: What is a data product, and why you should care

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