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Curiosity Software vs K2view

Amitai Richman

Amitai Richman,Product Marketing Director

In this article

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    Table of Contents

    Curiosity Software vs K2view
    6:06
    A detailed comparison of Curiosity Software vs K2view across test data management, data masking, and synthetic data generation, optimized for enterprise needs. 

    Overview of the 2 vendors 

    Curiosity Software and K2view both address the challenges of delivering secure, reliable, and production-like test data.  

    Curiosity offers an AI-driven test data generation tool designed to simplify discovery, analysis, and synthetic data generation for small teams and mid-market organizations.  

    K2view, by contrast, delivers an enterprise-grade test data management tool with a 5/5 Gartner Insights 12-month average peer review rating, engineered for large-scale test data management, data masking, and synthetic data generation across highly complex, multi-system environments. 

    While both vendors claim to accelerate test data readiness, they differ significantly in their architectural philosophies, depth of capabilities, and suitability for enterprise-grade workloads. 

    Comparison table 

    Here’s how the 2 vendors shape up: 

    Capability 

    Curiosity Software  

    K2view 

    K2view impact  

    Test data management 

    • AI-powered discovery and provisioning 

    • Supports data visibility, coverage analysis, and automated refreshes 

    • Best suited for simpler landscapes and departmental adoption 

    • Business entity approach hides multi-source complexity and enables fast, accurate, referentially complete provisioning 

      End-to-end capabilities: discovery, masking, subsetting, synthetic data, self-service delivery 

    • Integrates with any system for full test coverage 

    Leads the market in enterprise-scale TDM, speed to data, and accuracy across distributed systems 

    Data masking 

    • Masking is de-emphasized in favor of synthetic data 

    • Limited enterprise masking depth 

    • Suitable for small-scale, non-regulated masking needs 

    • Business entity masking ensures referential integrity and semantic consistency 

    • Inflight masking means no PII is stored at rest. Dozens of OOB functions, customizable 

    • Integrates with any source 

    • Foundation for TDM and SDG 

    Offers powerful, comprehensive, and compliance-ready data masking 

    Synthetic data generation 

    • AI-generated synthetic data emphasizes coverage and speed 

    • Best for targeted synthetic creation within smaller data scopes 

    • End-to-end lifecycle: 

    • Subset and mask training data, generate synthetic data, and orchestrate to downstream systems 

    • 4 generation methods: Rules, cloning, masking, GenAI 

    • Business entity approach, maintaining hierarchy and relationships across systems 

    Delivers an array of methods, accuracy, and enterprise-grade utility 

    K2view strengths 

    K2view stands out for enterprises seeking full-scale, production-grade test data management, test data provisioning, data masking, and synthetic data generation across complex ecosystems. Its defining differentiators include: 

    1.    Exceptional data fidelity via its business entity approach 

    This patented test data management approach restructures data around business entities (customer, order, device, etc.), ensuring that all related data from every system is delivered together – accurately, consistently, and with full referential integrity. The entity-based model dramatically improves TDM adoption, reduces data delivery time, and accelerates software release cycles. 

    2.    Future-proof data masking 

    K2view data masking ensures:  

    • In-flight protection, so no PII is ever exposed at rest  

    • Complete semantic consistency  

    • Flexible, customizable masking methods 

    • Seamless integration with any source system 

    3.    One stop shop

    A single solution handles:  

    • PII discovery  

    • Masking

    • Subsetting  

    • Synthetic data generation

    • Self-service data provisioning (subset, reserve, age, rollback, refresh, load) 

    4.    Synthetic data designed for enterprise utility

    K2view employs four generation modes – rules-based, cloning, masking-based, and GenAI – to support regression, new-functionality, performance, and scenario testing. Business-entity structure ensures the generated data maintains relationships across environments. 

    5.    Proven enterprise maturity 

    With a 5/5 Gartner Insights 12-month average peer rating, K2view is consistently recognized for reliability, performance, and real-world impact across global enterprises. 

    Curiosity Software suitability

    Curiosity provides several benefits to smaller teams and environments, including:  

    • Test data automation for departmental use  

    • Good fit for SMBs and less regulated environments  

    • Point tool for targeted synthetic data generation  

    • Suitability alongside other Curiosity tools 

    • Discovery, coverage analysis, and monitoring capabilities  

    • Simpler and more self-contained test data generation 

    These attributes make Curiosity a reasonable choice for firms with contained architectures and without stringent masking or enterprise-scale requirements. 

    Overall comparison 

    Both vendors address test data management challenges, but their focus differs: 

    • Curiosity centers on AI-driven sensitive data discovery and synthetic data
    • K2view delivers a deeply engineered, enterprise-class TDM product built for accuracy, compliance, and scale. 

    Where Curiosity simplifies test data workflows for smaller scopes, K2view excels in multi-source integration, advanced masking, and high-fidelity synthetic generation – ensuring complete, secure, and production-like test data across any environment.

    For enterprises needing consistent test data across multiple legacy and modern systems, K2view emerges as the clear choice, supporting Snowflake data masking, Workday data masking, mainframe data masking, Oracle data masking, Salesforce data masking, MongoDB data masking, and data masking tools for SQL Server – as well as SAP test data management tools – and more.

    Its breadth of capabilities, business entity architecture, and exceptional customer ratings provide unmatched speed, accuracy, and long-term value. 

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