Ubiq vs Thales CipherTrust
How identity-driven runtime data protection compares to centralized enterprise key management, so you can pick the right control for encrypting, tokenizing, and masking sensitive data.
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CMMC 2.0 Level 1Identity worked. Until data access stopped being direct.
The problem is no longer just who gets in. Sensitive data is now accessed by users, applications, APIs, service accounts, analytics tools, AI agents, and MCP workflows. Access paths are multiplying, but controls have not kept up. That runtime gap is where exposure happens.
System access is not sensitive data access
IAM and IGA help determine who can access a system. But access to the system does not answer what sensitive data that identity should be allowed to see, use, or expose at runtime.
AI creates indirect access to sensitive data
A user prompts an agent. The agent calls tools, APIs, databases, warehouses, and applications. Controls need to follow identity through the workflow, not stop at the original login.
Sensitive data has more consumers than ever
Apps, APIs, service accounts, analytics tools, AI agents, and automation jobs all consume sensitive data. The more consumers there are, the harder it becomes to control what each identity can actually see and use.
Access paths are multiplying
Sensitive data rarely stays in one place. It moves through workflows, tools, prompts, reports, exports, logs, and downstream systems. Each new access path creates another point where exposure can happen.
Ubiq closes the runtime gap by controlling what sensitive data each identity can see and use at the moment of access.
How Ubiq works
Same sensitive data. Different identities. Different runtime outcomes.
Ubiq evaluates the requesting identity, context, and policy at runtime, then returns only the representation that identity is authorized to see.
Access request
Protected employee record
- Employee ID
- EMP-3X9Q-1182
- Name
- Maria Chen
- mariac@acme.com
- Salary
- $142,800
Real-time evaluation
Runtime data outcome
HR app
Full viewAuthorized to process the employee record
Support analyst
MaskedNeeds to confirm the record, not read all fields
Analytics API
De-identifiedAuthorized for analysis without direct identifiers
AI agent
ProtectedOperates on protected values, never cleartext
Protected once. Resolved differently at runtime for each identity.
Ubiq vs Thales CipherTrust, capability by capability
Both platforms protect sensitive data. The difference is how each is deployed, integrated, and enforced across modern application, database, BI, and AI workflows.
| Capability | Thales CipherTrust | Ubiq |
|---|---|---|
| Identity-aware runtime cleartext authorizationDecide which users, services, and workflows can read sensitive values right now. | Partial | ✓ |
| Identity-governed runtime data outcomesReturn full, masked, de-identified, tokenized, or no data for the same record by identity, context, and policy. | Partial | ✓ |
| Access Graph across identities, access groups & datasetsMap which identities, access groups, and datasets are connected and how access flows between them. | – | ✓ |
| Anomalous sensitive-data access detectionSurface new identities, new access paths, and unusual dataset access. | – | ✓ |
| Field & record-level protectionEncrypt, tokenize, or mask individual values, not just storage. | ✓ | ✓ |
| SDK and API integration, live in minutesAdd a few lines of code across major languages, no appliances. | Partial | ✓ |
| No hardware, VMs, agents, or proxies to deployIntegrate through SDKs and APIs inside your own environment. CipherTrust adds key-management appliances, the CipherTrust Manager, and connector or proxy components in the data path. | – | ✓ |
| Enforcement across BI, pipelines & AI/RAG workflowsKeep values protected downstream across exports, notebooks, vector stores, MCP servers, and AI agents. | Partial | ✓ |
| Centralized enterprise key managementKMIP, Oracle TDE / SQL Server EKM, broad hybrid key control. | ✓ | Partial |
| Transparent at-rest / storage & file encryptionTDE-style protection for files, tablespaces, and backups. | ✓ | – |
| AI & vector search on protected dataKeep sensitive source data encrypted and identity-governed while AI and vector workflows run on derived representations that preserve similarity search. | – | ✓ |
| Sensitive-data discovery & classification | ✓ | ✓ |
| FIPS 140-2 Level 3 key storage, NIST-approved algorithms | ✓ | ✓ |
| Data never leaves your environmentOnly encrypt/decrypt key calls reach the platform. | Partial | ✓ |
Same data. Different identities. Different outcomes.
See identity-governed data access in the product
Ubiq shows you who and what is accessing protected data, how access flows from identities to datasets, and when access looks anomalous. Representative views of the Ubiq console.
Access Visibility
See protected vs unprotected records, active datasets, top identities, and anomalies across your data estate.
Records Protected
1.6B
Records Unprotected
670.5M
Active Datasets
25
Active Identities
Ubiq API keys
7
Active Identities
Integrated IdP
1
Use Cases Deployed
deployed
1 / 1
Protected Data Access
Top sensitive data accessed in the selected period
| Sensitive Data | Protected | Unprotected | Identities | Anomalies |
|---|---|---|---|---|
| SSNTop identity: Analytics Service | 77.1M | 41.1M | 4 | 2 |
| Account NumberTop identity: Reporting Service | 108M | 1.7M | 5 | 1 |
| Date of BirthTop identity: Data Pipeline | 16.7M | 1.7M | 3 | 0 |
| Free-text PIITop identity: Support Console | 8.8M | 8.8M | 2 | 0 |
Protection Activity
Last 7 daysAnomalous Events
Coming soon- 2m ago
First-time decrypt access to PAN
IAM Connect (service account)
- 16m ago
Unusual spike in SSN access
Analytics Service
- 32m ago
New identity accessing Tax ID
Data Pipeline (workload)
- 1h ago
Access from new location
BI Reporting
- 2h ago
Unusual access pattern to Account Number
App Backend
Top Identities
Last 7 days| Identity | Top Dataset | Records | Anomalies |
|---|---|---|---|
| Analytics Service | SSN | 499.3M | 2 |
| Reporting Service | Account Number | 312.0M | 1 |
| Data Pipeline | Date of Birth | 88.4M | 0 |
Access Graph
Trace how each identity resolves through an access group to the exact datasets it can reach.
The highlighted path shows one identity resolving through its identity group and access group to the exact datasets it can reach.
Where each one fits
Where Thales CipherTrust leaves a runtime gap
CipherTrust centralizes key management and encrypts data at rest, but it does not decide what sensitive data each identity can see and use at the moment of access.
- No identity-governed runtime outcomes: it cannot return full, masked, de-identified, or tokenized data for the same record by identity and context.
- Appliance- and agent-based deployment adds operational overhead before any data is protected.
- No Access Graph or anomalous-access detection across identities, access groups, and datasets.
- Protection does not follow data into BI, pipelines, vector stores, MCP servers, and AI agents.
Why teams choose Ubiq
Ubiq controls what sensitive data each identity can see and use, at runtime, across the modern application and data workflows where your data already lives.
- Encrypt, tokenize, or mask sensitive fields with a few lines of code, live in minutes, no agents or proxies.
- Enforce cleartext access by identity, role, and context across apps, databases, BI tools, pipelines, and AI/RAG workflows.
- Keep values protected downstream when copied, exported, logged, embedded, or consumed by another system.
- See who and what is accessing protected data with access visibility, an Access Graph, and anomalous-event detection.
- Deploy inside your own environment so customer data never leaves your control.
- Simple use-case-based pricing: license the use cases you need, with unlimited protect and unprotect operations in scope.
How to evaluate a sensitive data protection platform
Use these questions to compare any option, including Ubiq, against the runtime exposure you actually need to close.
- Can it decide what sensitive data each identity sees at runtime, not just who can log into a system?
- Does protection follow the data across apps, databases, warehouses, BI tools, pipelines, and AI/RAG workflows?
- Can it return a different outcome for the same record, full, masked, de-identified, tokenized, or none, by identity, context, and policy?
- Does it control what AI agents, MCP servers, and vector stores can access on a user's behalf?
- Can it show who and what is accessing protected data with access visibility, an access graph, and anomalous-event detection?
- Do protected values stay protected downstream when copied, exported, logged, embedded, or indexed?
- How fast can engineers integrate it, and does it require agents, proxies, or appliances?
- Does sensitive data ever leave your own environment?
Frequently asked questions
What is the difference between Ubiq and Thales CipherTrust?
Thales CipherTrust is a broad enterprise platform centered on centralized key management and transparent at-rest encryption. Ubiq is identity-driven runtime data protection that encrypts, tokenizes, or masks individual values and governs who can read them in cleartext across applications, databases, BI tools, and AI workflows.
Is Ubiq better than Thales CipherTrust?
Ubiq is the better choice when you need to control what sensitive data each identity can see and use at runtime across applications, databases, BI tools, and AI workflows, integrated in minutes with no agents or proxies. Centralized key management and at-rest encryption protect where data is stored but never decide what an identity can read at the moment of access, which is the runtime gap Ubiq closes.
Can Ubiq replace Thales CipherTrust?
Ubiq can replace CipherTrust for application-level encryption, tokenization, masking, sensitive-data discovery and classification, and runtime access enforcement. Where teams keep legacy key management or at-rest encryption in place, Ubiq layers identity-governed runtime data protection on top and can take over in phases.
Can Ubiq run AI and vector search on sensitive data without exposing it?
Yes. Ubiq separates protection of sensitive source data from vector computation. Sensitive records and identifiers stay strongly encrypted and identity-governed, while AI and vector workflows operate on derived representations in a controlled way that preserves similarity search. Teams can enable AI-driven search and analysis without exposing plaintext or weakening their encryption posture.
How does Ubiq control what AI agents and MCP workflows can access?
Ubiq governs sensitive data at the point of access, so when an AI agent, MCP server, RAG pipeline, or vector store requests data on a user's behalf, Ubiq evaluates the calling identity, context, and policy and returns full, masked, de-identified, tokenized, or no data. Protected values stay protected when embedded, indexed in a vector store, or consumed by a downstream agent.