Voltage SecureData vs Ubiq

Executive Summary

OpenText Voltage SecureData, now part of OpenText’s broader data privacy and protection portfolio, provides established enterprise data protection capabilities for protecting sensitive data across complex environments. Its capabilities include format-preserving encryption, tokenization, masking, hashing, centralized policy, key management, and enterprise-scale data protection patterns.

These capabilities are valuable, especially for organizations that need format-preserving encryption, enterprise tokenization, legacy application compatibility, centralized data protection policy, and broad data protection coverage across regulated environments.

Ubiq addresses the same overall sensitive data protection problem with a different architecture and operating model. Ubiq is designed as a focused runtime sensitive data protection platform that protects sensitive values directly and governs whether users, applications, service accounts, APIs, pipelines, BI tools, AI workflows, and downstream systems can access those values in cleartext at runtime.

The key distinction is not whether both platforms protect sensitive data. They do.

The key distinction is how they are deployed, integrated, operated, and extended across modern application, database, warehouse, API, BI, pipeline, and AI workflows.

Voltage SecureData is an established enterprise data protection platform with strong capabilities around format-preserving encryption, tokenization, masking, hashing, key management, and centralized control. Depending on the deployment model, Voltage implementations may involve centralized services, policy infrastructure, integration components, application changes, proxies, gateways, or other enterprise deployment patterns.

Ubiq is a single runtime data protection platform designed to integrate through software libraries, APIs, database and warehouse integrations, BI patterns, and AI/data workflow enforcement without requiring a heavy infrastructure footprint.

Ubiq also supports modern AI, RAG, and vector-driven workflows by separating protection of sensitive source data from AI/vector computation. Sensitive records and identifiers can remain protected and identity-governed, while AI workflows operate on controlled derived representations that preserve semantic search, retrieval, and analysis functionality without broadly exposing plaintext sensitive values.

Key Takeaways

• OpenText Voltage SecureData and Ubiq both help protect sensitive data, but they differ significantly in architecture, deployment model, operational complexity, and runtime enforcement approach.
• Voltage SecureData is strong for format-preserving encryption, tokenization, masking, hashing, centralized control, key management, and established enterprise data protection use cases.
• Voltage deployments may involve multiple enterprise components, centralized policy services, integration patterns, infrastructure planning, and operational ownership depending on the use case.
• Ubiq is designed as a focused runtime sensitive data protection platform with software libraries, APIs, and data workflow integrations that are easier for application, data engineering, analytics, and security teams to deploy and operate.
• Ubiq protects selected sensitive values and controls whether an identity or workflow can access those values in cleartext at runtime.
• Ubiq is especially useful when organizations need field and record-level enforcement across applications, databases, warehouses, APIs, service accounts, pipelines, BI tools, AI/RAG workflows, exports, and downstream systems.
• Ubiq can also support AI/vector-driven workflows where traditional encryption or tokenization may break semantic meaning, similarity search, or vector-based computation if applied directly to the values the AI workflow needs to interpret.

Where OpenText Voltage SecureData Helps

OpenText Voltage SecureData provides enterprise data protection capabilities for sensitive data across complex environments.

Its capabilities can help teams:

• Protect sensitive fields with format-preserving encryption
• Tokenize sensitive values
• Use enterprise tokenization patterns
• Apply masking or hashing where appropriate
• Preserve data formats for legacy applications and databases
• Centrally manage data protection policies
• Centrally manage cryptographic keys
• Protect regulated data such as payment, customer, healthcare, financial, and identity data
• Support compliance and privacy requirements
• Integrate data protection across hybrid IT environments
• Support environments where application changes may need to be minimized
• Support systems where preserving existing field formats is important

These capabilities are valuable for enterprise data protection programs.

They help answer questions such as:

• Which sensitive fields require encryption, tokenization, masking, or hashing?
• Which values need format preservation?
• How can protected data remain usable in legacy systems?
• Which policies should apply to protected fields?
• How should keys be managed centrally?
• How can sensitive data be protected across regulated environments?
• How can existing applications continue operating when sensitive values are protected?

For organizations with established Voltage deployments, Voltage SecureData can provide proven data protection patterns for regulated enterprise workloads, especially where format preservation and legacy compatibility are important.

Where Ubiq Is Different

Ubiq is focused on runtime sensitive data protection.

That means Ubiq is designed to answer a specific operational question:

Should this user, application, service account, pipeline, BI tool, AI workflow, or downstream system receive this sensitive value in cleartext right now?

Ubiq protects selected sensitive fields and records, then enforces cleartext access through identity-aware policy at runtime.

This allows organizations to:

• Protect sensitive values directly
• Govern cleartext access by identity, role, application, dataset, and context
• Apply protection across applications, databases, warehouses, APIs, BI tools, pipelines, and AI workflows
• Restrict cleartext access for service accounts and automation
• Reduce exposure in BI and analytics workflows
• Support AI, RAG, notebook, MCP, agent, and vector-driven workflows without broadly exposing sensitive plaintext
• Preserve protection when data is copied, exported, embedded, indexed, replicated, or consumed downstream
• Maintain separation between system access and sensitive value authorization
• Separate protection of sensitive source data from controlled AI/vector computation where semantic functionality is required

The difference is not that Voltage protects data and Ubiq does not, or vice versa.

The difference is that Voltage SecureData is an established enterprise data protection platform, while Ubiq is a focused runtime data protection layer designed to be easier to integrate and operate across modern software and data workflows.

Comparison Matrix

Key Architectural Differences

Established Enterprise Data Protection vs Focused Runtime Data Protection

Voltage SecureData is an established enterprise data protection platform.

It is well known for format-preserving encryption, tokenization, masking, hashing, centralized policy, and key management.

That strength can be valuable, especially when an organization needs format preservation, legacy application compatibility, or mature enterprise tokenization and encryption patterns.

However, established enterprise data protection platforms can also require broader planning and operational coordination. Depending on the use case, organizations may need to plan around centralized services, policy infrastructure, key management, integration components, proxies, gateways, application changes, operational ownership, and ongoing administration.

Ubiq is intentionally more focused.

Ubiq’s core question is:

Which identities and workflows should be able to access selected sensitive values in cleartext?

Ubiq is designed to protect sensitive values and enforce runtime cleartext access through software libraries, APIs, database integrations, warehouse integrations, BI patterns, and AI/data workflow enforcement.

This makes Ubiq easier to implement in modern application and data environments where teams need field and record-level runtime protection without deploying a broader enterprise data protection platform first.

Format-Preserving Encryption and Tokenization vs Runtime Cleartext Authorization

Voltage SecureData has deep roots in format-preserving encryption and tokenization.

These capabilities are useful when protected values must retain their original structure for legacy systems, databases, payment workflows, or regulated applications.

Ubiq also supports data protection methods such as encryption, tokenization, and masking.

The architectural difference is the emphasis on runtime cleartext authorization.

With Ubiq, the question is not only:

Which fields should be encrypted or tokenized?

The question becomes:

Is this user, application, service account, API, pipeline, BI tool, or AI workflow allowed to see this sensitive value in cleartext right now?

That distinction is especially important when many identities and workflows touch the same data but should not receive the same level of cleartext access.

Multiple Components and Deployment Patterns vs One Runtime Protection Platform

Voltage deployments can involve multiple enterprise components depending on the desired outcome.

For example, a deployment may involve:

• Format-preserving encryption
• Tokenization
• Masking
• Hashing
• Centralized policy
• Key management
• Application integration
• Proxy or gateway-style integration patterns
• Enterprise infrastructure planning
• Operational administration

Those capabilities are powerful, but they may also require architecture planning, procurement decisions, deployment coordination, infrastructure ownership, operational monitoring, and ongoing platform administration.

Ubiq is designed as one runtime sensitive data protection platform.

Instead of requiring teams to assemble and operate multiple components to protect sensitive values across workflows, Ubiq provides a single protection model for:

• Encryption
• Tokenization
• Masking
• Identity-aware policy enforcement
• Field and record-level cleartext authorization
• Application, database, warehouse, API, BI, pipeline, and AI workflow integrations

This difference matters when the goal is to protect sensitive values quickly and consistently across modern systems without adding unnecessary operational complexity.

Complex Integration Patterns vs Software Libraries and Simple APIs

Voltage can support enterprise integration patterns for applications, databases, and data workflows, but those patterns may involve centralized services, policy infrastructure, proxies, gateways, application changes, key management components, or platform-specific integrations.

That is often appropriate for legacy systems, regulated environments, format-preserving requirements, or large enterprise data protection programs.

Ubiq is designed for software and data workflow integration.

Ubiq can be embedded where sensitive data is created, queried, transformed, analyzed, or consumed through:

• Software libraries
• Simple APIs
• Application integration
• Database integration
• Warehouse integration
• BI integration patterns
• Data pipeline workflows
• AI and RAG workflows

This is a major operational difference.

With Ubiq, application, data, analytics, and security teams can focus on the actual data protection questions:

• Which fields or records need protection?
• Which identities can see cleartext?
• Which applications or workflows need enforcement?
• What should service accounts receive?
• What should BI users see?
• What should AI workflows receive?
• What happens when data is copied, exported, or consumed downstream?

They do not need to start by deploying a broad data protection platform footprint before enforcing runtime protection.

AI and Vector Workflows Without Broad Plaintext Exposure

AI, RAG, and vector search workflows create a difficult data protection challenge.

Data teams often want to run semantic search, similarity matching, retrieval, model enrichment, or agent workflows on sensitive data. But traditional encryption or tokenization can break semantic meaning, similarity search, or vector-based computation if applied directly to the values the AI workflow needs to interpret.

Ubiq supports this by separating protection of sensitive source data from AI/vector computation.

Sensitive source records, identifiers, and regulated fields can remain protected and identity-governed, while AI/vector workflows operate on controlled derived representations that preserve the functionality required for semantic search, retrieval, or analysis.

This allows organizations to support AI-driven workflows without broadly exposing plaintext sensitive data or weakening the protection model around the original sensitive values.

This is especially important for regulated data environments where teams want to enable AI use cases but cannot simply decrypt, copy, or expose raw sensitive values into notebooks, vector stores, RAG pipelines, model workflows, or downstream AI systems.

Centralized Enterprise Platform vs Workflow-Level Runtime Enforcement

Voltage SecureData is commonly deployed as part of an enterprise data protection program with centralized policy, key management, and integration planning.

That approach can be appropriate for large regulated environments, especially where there are existing Voltage deployments or legacy format-preserving requirements.

However, application and data teams may experience that model as heavier if they need to coordinate with platform owners, configure centralized services, align key management, modify integration paths, and wait for shared infrastructure before protecting sensitive fields.

Ubiq is designed to be easier for application, data engineering, analytics, and security teams to deploy and operate directly in the workflows where sensitive data is actually used.

That means teams can protect sensitive values through familiar implementation patterns rather than routing every use case through a large centralized infrastructure project.

This matters when organizations need to move quickly across:

• Modern applications
• APIs
• Warehouses
• Databases
• Data pipelines
• BI tools
• AI and RAG workflows
• Downstream systems

Traditional Data Protection Programs vs Modern AI and Analytics Workflows

Voltage SecureData has long been used in enterprise environments with structured data, legacy applications, and regulated workloads.

Ubiq is designed around the modern reality that sensitive data is accessed by more than traditional applications and databases.

Sensitive values may be used by:

• Warehouses
• BI tools
• Data pipelines
• Event streams
• APIs
• RAG systems
• AI agents
• MCP tools
• Notebooks
• Vector stores
• Downstream replicas
• Vendor feeds

Ubiq is built to enforce sensitive value access across these runtime paths, not only inside a traditional application or database control point.

How Ubiq Differentiates from OpenText Voltage SecureData

Ubiq differentiates from Voltage SecureData through a focused runtime enforcement model for sensitive values and a lighter operational model.

With Ubiq, selected sensitive fields can remain encrypted, tokenized, masked, or otherwise protected by default. Cleartext access is granted only when the requesting identity or workflow is authorized by policy at runtime.

This allows organizations to:

• Protect sensitive values across applications, databases, warehouses, APIs, and analytics workflows
• Control cleartext access for users, applications, service accounts, pipelines, and AI systems
• Reduce exposure in BI and reporting workflows
• Protect sensitive data used by AI, RAG, notebook, model, agent, and vector-driven workflows
• Preserve protection when data is copied, exported, embedded, indexed, replicated, or consumed downstream
• Maintain separation between system access and sensitive value authorization
• Separate sensitive source data protection from controlled AI/vector computation
• Integrate sensitive data protection into modern software and data workflows
• Avoid unnecessary platform complexity when the primary requirement is runtime sensitive value protection

In this model:

• Voltage SecureData provides established enterprise FPE, tokenization, masking, hashing, key management, and centralized data protection controls.
• Ubiq provides focused runtime sensitive value protection with identity-aware cleartext enforcement and simpler software-based integration patterns.
• Ubiq can also support AI/vector-driven workflows by allowing sensitive source data to remain protected while controlled derived representations support semantic search, retrieval, and analysis.

The right choice depends on the customer’s architecture, incumbent systems, deployment preferences, legacy compatibility requirements, AI/data workflow needs, and the level of identity-aware runtime enforcement required.

Internal Evaluation Questions

When evaluating OpenText Voltage SecureData and Ubiq, teams should ask:

• Are we looking for an established enterprise data protection platform or focused runtime sensitive data protection?
• Do we have existing Voltage SecureData deployments that should remain in place?
• Which sensitive fields require format-preserving encryption or tokenization?
• Which sensitive fields require identity-aware cleartext authorization at runtime?
• Which workflows receive sensitive data in cleartext today?
• Which users, applications, service accounts, APIs, pipelines, BI tools, and AI workflows can access sensitive values today?
• How much infrastructure are we willing to deploy and operate?
• Do we need legacy FPE compatibility, or do we need software-based integration into modern applications and data workflows?
• Which use cases require centralized data protection services, proxies, gateways, or platform-specific integration patterns?
• Which use cases simply require field and record-level runtime protection?
• What happens when sensitive data is exported, copied, logged, joined, materialized, embedded, indexed, or replicated?
• Do BI tools, dashboards, extracts, and reports expose sensitive values?
• Do AI, RAG, notebook, MCP, vector store, model training, model inference, or agent workflows access sensitive values?
• Do we need semantic search, similarity matching, retrieval, enrichment, or vector workflows on sensitive data?
• Would direct encryption or tokenization of sensitive values break semantic interpretation or vector-based computation?
• Can sensitive source records and identifiers remain protected while AI/vector workflows operate on controlled derived representations?
• Should service accounts, APIs, pipelines, or automation workflows receive cleartext, or only protected values?
• Which control determines whether a specific identity or workflow can see sensitive values in cleartext?
• Does the protection model need to work across platforms beyond a single application, database, storage system, warehouse, or AI workflow?

Summary

OpenText Voltage SecureData provides established enterprise data protection capabilities for format-preserving encryption, tokenization, masking, hashing, key management, and centralized control.

Ubiq addresses the same overall data protection problem with a focused runtime sensitive data protection model and a simpler software-based integration approach.

By protecting selected sensitive values directly and governing cleartext access through identity-aware policy, Ubiq helps organizations reduce exposure across users, applications, service accounts, APIs, pipelines, databases, warehouses, BI tools, AI workflows, exports, and downstream systems.

Ubiq also helps organizations support AI, RAG, and vector-driven workflows where teams need semantic search, retrieval, or analysis without broadly exposing sensitive source values in plaintext or weakening encryption posture.

Voltage SecureData is an established enterprise data protection platform.

Ubiq is a focused runtime sensitive value protection layer.

Voltage SecureData is often the better fit when the primary need is legacy format preservation, established enterprise tokenization, centralized data protection infrastructure, or an existing Voltage program.

Ubiq is often the better fit when the primary need is easier deployment, lower operational overhead, software-based integration, identity-aware runtime enforcement, and AI/vector workflow support across modern data workflows.

The best fit depends on architecture, deployment model, workflow coverage, legacy compatibility needs, AI/data workflow requirements, and the level of identity-aware runtime enforcement required.