At a glance
| Supported databases | Relational and NoSQL databases, mainframe, SaaS apps, message queues, files and cloud stores (no per-engine matrix on the pages checked) |
| Auditing and activity monitoring | Not an activity monitoring product |
| Masking | Static and dynamic masking, entity-level referential integrity, unstructured data |
| Encryption or tokenization | Reversible pseudonymization and tokenization |
| Privileged access | Not applicable |
| Policy enforcement | Masking functions and policies applied during provisioning |
| Data volume or subsetting | Entity-based subsets by business attributes; reservation and rollback |
| Deployment | On premises, cloud or hybrid; K2cloud portal for Fabric releases |
| Licensing | Commercial, quote only; "Start Free" option with unstated terms |
K2view suits enterprises whose test data spans many systems (CRM, billing, mainframe, SaaS) and must stay consistent for each customer or account. Its entity-based approach gives self-service subsets with masking applied in flight. It is a broad platform with quote-only pricing, so it pays off in complex landscapes rather than for one database.
Overview
K2view builds its products on the K2view Data Product Platform (the Fabric runtime), which stores data for each business entity, for example one customer, account or order, in its own Micro-Database. Test Data Management and Data Masking are solutions on that platform, alongside synthetic data, tokenization, data integration and AI context products. The support site lists Fabric 8.5.2 as the latest release and a K2cloud portal for deploying Fabric releases.
For test data, K2view subsets by business attributes (for example account status or balance) and returns the complete data for each selected entity across all systems, rather than following table joins in one database. Teams provision data through a self-service portal, API or agent, reserve entities so tests do not overwrite each other, and snapshot and roll back to a known state. Masking discovers sensitive data with rules and LLMs, masks it statically or dynamically in flight, keeps referential integrity at entity level and also covers unstructured content such as PDFs and images.
Key features
- Entity-based test data subsetting by business attributes, across many source systems
- Self-service provisioning by portal, API or agent, with data reservation
- Snapshots, versioning and rollback of test data to a known-good state
- Discovery and classification of PII using rules and large language models
- Static and dynamic masking in flight, with entity-level referential integrity and tokenization
- Masking of unstructured content such as documents, PDFs and images
- Synthetic data from AI, rules or entity cloning for new features and negative tests
Integrations and ecosystem
Pros and cons
Pros
- Keeps each customer's data consistent across many systems in test environments
- Testers can request, reserve and roll back data themselves
- Masking, tokenization, synthetic data and subsetting in one platform
- Covers unstructured content as well as tables
Cons
- No public pricing
- The entity model must be designed up front, which takes effort
- No database-by-database support matrix on the public product pages
- A broad platform that may be more than a single-database team needs
Pricing
K2view publishes no prices for Data Masking or Test Data Management. The website offers "Start Free", a product tour and a demo request, but the terms of the free start are not stated on the pages checked. Enterprise use is by quote.
Pricing checked on the vendor's official page on 7 November 2026. Prices change; confirm before buying.
Who it is best for
Enterprises with complex application landscapes that need consistent, masked, self-service test data per customer or account across many systems.
Typical use cases
- Provision a masked test set of 500 customers whose data spans CRM, billing and mainframe
- Reserve test entities so parallel test teams do not overwrite each other
- Mask PII in documents and PDFs consistently with the related database records
- Generate synthetic customers for a feature that has no production data yet
Who should look elsewhere
- Teams that want full virtual copies of one large database: see Perforce Delphix.
- Teams that only need to mask copies they already make: see DataMasque.
Verdict
K2view takes a distinctive entity-based approach to test data and masking that works well when one customer's data lives in many systems. The cost is up-front modelling and quote-only licensing; for a single database, a simpler masking or virtualization tool may be enough.
Frequently asked questions
Are K2view Data Masking and Test Data Management separate products?
They are separate solutions on the same K2view Data Product Platform. Test Data Management uses the masking capabilities when it provisions data, and Data Masking can also be used for analytics, data sharing and AI workloads.
How is K2view different from Delphix?
K2view organises data by business entity and provisions entity-based subsets across systems, with masking in flight, reservation and rollback. Delphix delivers full virtual read/write copies of whole databases and masks them, with rewind and bookmarks.
Does K2view mask unstructured data?
Yes. K2view says it masks sensitive data in images, documents, presentations and PDFs and keeps it consistent with the related structured data.
How much does K2view cost?
K2view does not publish prices. The site offers a "Start Free" option and demos; enterprise licences are by quote.
Sources
Checked November 2026.
Listed in: Database Security & Auditing, Database Testing & Test Data.
How we research reviews and what star ratings mean: our editorial method.