PostgreSQL vs Ubiq

Executive Summary

PostgreSQL provides strong native security and extensibility controls for relational database environments. These include roles, privileges, column-level grants, row-level security policies, SSL/TLS, auditing extensions, and cryptographic functions through pgcrypto.

These controls are valuable and should remain part of the architecture.

PostgreSQL-native controls address important parts of the database security model. Roles and privileges govern who can access database objects. Column-level grants can restrict access to specific columns. Row-level security policies can restrict which rows are visible or modifiable. pgcrypto can support encryption and hashing workflows inside PostgreSQL.

Ubiq addresses a different layer of the problem: protecting sensitive values themselves and governing whether users, applications, service accounts, APIs, pipelines, BI tools, AI workflows, and downstream systems can access those values in cleartext at runtime.

The strongest model is layered. Use PostgreSQL-native controls for database access control, query governance, row and column restrictions, transport security, and database operations. Use Ubiq for identity-aware runtime protection of sensitive fields and records across PostgreSQL and broader enterprise workflows.

Key Takeaways

• PostgreSQL-native security and Ubiq runtime sensitive data protection solve different problems and should be viewed as complementary controls.
• PostgreSQL is strong for roles, privileges, column-level grants, row-level security, database functions, and extensible security controls.
• Ubiq protects selected sensitive values directly and controls whether an identity or workflow can access those values in cleartext at runtime.
• PostgreSQL policies generally govern database access and query behavior inside PostgreSQL. Ubiq helps protect sensitive values before, inside, and beyond PostgreSQL.
• Ubiq is especially useful when organizations need to reduce cleartext exposure across applications, service accounts, APIs, pipelines, BI tools, AI/RAG workflows, exports, logs, and downstream systems.

Control Boundary View

Where PostgreSQL Native Security Helps

PostgreSQL provides important native controls for securing relational data and database operations.

These controls help teams:

• Authenticate users, applications, and services
• Authorize access through roles and privileges
• Grant or revoke access to databases, schemas, tables, views, functions, sequences, and columns
• Restrict access to specific columns through column-level privileges
• Apply row-level security policies to restrict which rows are visible or modifiable
• Use views and functions to expose controlled data access paths
• Use SSL/TLS to protect data in transit
• Use pgcrypto for hashing, encryption, and decryption functions
• Extend security and audit behavior through extensions and managed service integrations
• Use cloud-provider encryption at rest when PostgreSQL is deployed through managed database services

These capabilities are valuable for PostgreSQL database security.

They help answer questions such as:

• Which users or roles can access this database, schema, table, view, function, or column?
• Which rows should this role be able to see or modify?
• Which columns should be restricted?
• Which functions should users be allowed to execute?
• How should data be protected in transit?
• Which fields should be encrypted or hashed using database functions?
• Which users or roles performed database operations?

For many PostgreSQL workloads, these controls are necessary and effective.

However, they are primarily PostgreSQL database controls. They govern access, permissions, query behavior, and database-side encryption functions within PostgreSQL-controlled paths.

Where PostgreSQL Native Security Is Not Designed to Go

PostgreSQL-native controls are not designed to provide persistent, identity-aware protection of sensitive values across every workflow where data may move or be consumed.

This distinction matters because sensitive data often does not stay inside one PostgreSQL access path.

Sensitive values may be accessed, copied, transformed, exported, joined, materialized, logged, embedded, or consumed by:

• Internal users
• Developers
• Database administrators
• Application services
• Service accounts
• APIs
• ETL and ELT pipelines
• CDC and event streaming workflows
• BI tools
• Reporting systems
• Data science notebooks
• AI and RAG workflows
• MCP-based tools and agents
• Vector stores
• Vendor feeds
• CSV, JSON, Excel, Parquet, or database exports
• Downstream databases
• Replicated datasets
• Temporary development or test environments

PostgreSQL can govern access inside PostgreSQL. But once sensitive values are returned in cleartext to an authorized session, decrypted by an application or database function, copied downstream, exported, logged, embedded into another system, or consumed by a separate workflow, PostgreSQL-native controls may no longer be the enforcement point.

That is the architectural gap Ubiq is designed to address.

Comparison Matrix

Key Architectural Differences

Database Access Control vs Sensitive Value Protection

PostgreSQL-native controls govern access to database objects and query results.

Ubiq protects selected sensitive values themselves.

This difference is important.

A user, role, application, or service account may have legitimate access to a PostgreSQL table, view, or function but should not necessarily see every sensitive value in cleartext. Ubiq allows organizations to protect sensitive fields and records directly, then decide at runtime whether a specific identity or workflow is authorized to receive cleartext.

Row and Column Policies vs Runtime Cleartext Authorization

PostgreSQL row-level security and column-level privileges are powerful database controls. They help determine which rows and columns a role can access through PostgreSQL.

Ubiq adds a separate runtime cleartext authorization model.

With Ubiq, the question is not only:

Is this role allowed to query this table, row, column, view, or function?

The question becomes:

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

That distinction matters when sensitive values are accessed across many workflows, not just one governed database query path.

Database Functions vs Independent Sensitive Value Enforcement

PostgreSQL pgcrypto can be used to encrypt, decrypt, hash, and verify data through database functions.

This can be useful for PostgreSQL-specific encryption workflows.

However, database-function-based protection depends on how applications, roles, functions, permissions, and keys are designed. If a user or application can call a decrypt function or access cleartext after decryption, PostgreSQL itself may not provide a broader identity-aware runtime policy layer across other systems.

Ubiq provides a separate sensitive value protection model that can be used consistently across applications, databases, APIs, BI tools, AI workflows, and downstream systems.

PostgreSQL Boundary vs Downstream Persistence

PostgreSQL-native controls are strongest while data remains inside PostgreSQL-controlled access paths.

But sensitive data often moves.

It may be exported to files, copied into downstream systems, replicated into analytics platforms, written into logs, joined into derived datasets, consumed by BI tools, embedded into vector stores, or used by AI workflows.

Ubiq helps maintain protection of selected sensitive values beyond a single PostgreSQL database boundary. If protected values are copied, exported, embedded, indexed, or consumed downstream, they can remain protected unless an authorized runtime path reveals cleartext.

Database Roles vs Identity-Aware Field and Record Controls

PostgreSQL uses roles, privileges, grants, row-level security policies, column privileges, views, and functions to determine database access.

Ubiq can apply identity-aware policy at the field and record level.

This makes it possible to apply more precise controls for:

• Different application users using the same backend service
• Different applications accessing the same table
• Different service accounts with different cleartext needs
• Different APIs exposing different sensitive fields
• Different BI users with different authorization levels
• AI workflows that should not receive raw sensitive values
• Downstream systems that should process protected values only

PostgreSQL-Specific Controls vs Cross-Platform Enforcement

PostgreSQL-native security is designed for PostgreSQL.

Ubiq is designed to protect sensitive values across broader enterprise data workflows, including applications, databases, warehouses, APIs, BI tools, pipelines, event streams, notebooks, and AI systems.

This matters when PostgreSQL is one part of a larger data environment.

In many organizations, PostgreSQL may be a critical operational database, but sensitive values may also appear in data warehouses, data lakes, analytics tools, APIs, event streams, AI workflows, vendor feeds, and downstream applications.

Ubiq provides a consistent sensitive value protection model across those paths.

When to Use Both

PostgreSQL-native security and Ubiq are not mutually exclusive.

Organizations should continue using PostgreSQL-native controls for:

• Authentication and authorization
• Roles and privileges
• Schema, table, view, function, sequence, and column grants
• Row-level security policies
• Views and stored functions
• SSL/TLS for data in transit
• Database auditing and logging
• pgcrypto where PostgreSQL-specific cryptographic functions are appropriate
• Managed-service encryption at rest where PostgreSQL is deployed through a cloud provider

Ubiq should be considered when organizations also need to:

• Protect sensitive values directly across PostgreSQL and non-PostgreSQL systems
• Govern cleartext access by identity, role, application, dataset, and context
• Apply consistent protection across applications, APIs, pipelines, BI tools, and AI workflows
• Limit blast radius from compromised database credentials, application credentials, service accounts, tokens, or API keys
• Restrict cleartext access for non-human identities and automation
• Protect sensitive values used by BI, AI, RAG, notebooks, agents, and downstream systems
• Maintain protection when data is copied, exported, embedded, indexed, logged, replicated, or consumed outside PostgreSQL
• Apply field- and record-level cleartext controls across multiple platforms

The layered model is simple:

• Use PostgreSQL for PostgreSQL-native access control and database security.
• Use Ubiq for runtime sensitive value protection across broader workflows.

How Ubiq Complements PostgreSQL

Ubiq complements PostgreSQL by protecting sensitive values before, inside, and beyond PostgreSQL workflows.

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:

• Store protected sensitive values in PostgreSQL
• Control cleartext access for users, applications, service accounts, APIs, and pipelines
• Reduce exposure in analytics, BI, and reporting workflows
• Protect sensitive data used by AI, RAG, notebook, model, and agent workflows
• Preserve protection when data is copied, exported, embedded, indexed, logged, replicated, or consumed downstream
• Maintain separation between PostgreSQL database access and sensitive value authorization
• Apply consistent protection across PostgreSQL and other enterprise data platforms

In this model:

• PostgreSQL governs database access, privileges, policies, functions, and database-specific security controls.
• Ubiq governs which identities and workflows can access selected sensitive values in cleartext.

Together, they provide a stronger security architecture than either approach provides alone.

Internal Evaluation Questions

When evaluating PostgreSQL-native controls and Ubiq together, teams should ask:

• Which sensitive fields require protection beyond standard PostgreSQL roles and privileges?
• Which users, roles, applications, service accounts, and APIs can access sensitive values today?
• Which workflows receive sensitive data in cleartext?
• Are row-level security and column-level privileges sufficient for the sensitive data exposure risk?
• Are any database functions or application paths decrypting sensitive values?
• 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 outside PostgreSQL?
• Do AI, RAG, notebook, MCP, vector store, model training, model inference, or agent workflows access sensitive values?
• Should service accounts, APIs, or automation workflows receive cleartext, or only protected values?
• How would the organization reduce blast radius if PostgreSQL credentials, application credentials, service accounts, tokens, or API keys are compromised?
• Which control determines whether a specific identity or workflow can see sensitive values in cleartext?
• Does sensitive value protection need to work across platforms beyond PostgreSQL?

Summary

PostgreSQL provides strong native security and extensibility controls for PostgreSQL environments. These controls are important for managing roles, privileges, row-level security, column-level access, views, functions, cryptographic operations, transport security, and database activity.

Ubiq addresses a different layer: runtime sensitive data protection across PostgreSQL and broader enterprise workflows.

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

PostgreSQL controls database access and query behavior.

Ubiq controls exposure of sensitive values across identities and workflows.

The strongest architecture uses both.