Windocks vs Delphix

Windocks is a modern alternative to Delphix that is implemented in days, at half the cost.

 

"Modern IT is defined by cloud computing.  It relies on standard servers, and scales with pay-as-you-go economics.  Expensive, proprietary storage for database virtualization is simply outdated," said a smart CIO.

Windocks was founded in 2015 and is recognized by Gartner for innovation in database virtualization, synthetic data, and Agentic AI powered analytics data. Delphix was founded in 2008 and sold to Perforce in 2024. We receive a growing number of inquiries about migration from Delphix, and are happy to share the similarities and differences between Windocks and Delphix.

 

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Explore Windocks capabilities

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Database Cloning

Create writable copies of databases in seconds instead of hours. Enable fast development, testing, and analytics, helping teams work efficiently with full, realistic environments without impacting production systems.

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SQL Server containers

Run multiple isolated SQL Server instances on a single machine using Docker Windows containers. Maximize hardware utilization, simplify testing and deployment, and provide great support for remote teams.

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Synthetic data

Generate synthetic data that reflects source distributions in databases or flat files.  Protect sensitive data by replacing Personally Identifiable Information (PII) like names, phone numbers, and addresses, to ensure regulatory compliance. 

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Feature Data

Code free data aggregation, cleansing, and enriching from multiple sources to create “features” for Machine Learning and AI. Feature data enables advanced analytics and ML modeling, such as predicting fraudulent transactions, improving decision-making, and driving business outcomes.

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Single source of truth

Combine data from multiple databases into a unified “feature data table.” This provides accurate, consolidated information across systems, eliminates duplication, and ensures consistent reporting for analytics, compliance, and business intelligence needs.

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Database subsetting

Reduce large databases to smaller, targeted datasets while maintaining all key relationships and integrity between tables. Subsetting helps accelerate testing, minimizes storage requirements, and protects sensitive information during development activities.

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