AWS DynamoDB vs Ubiq

Executive Summary

Amazon DynamoDB provides strong native security and governance controls for AWS-managed NoSQL workloads. These include AWS IAM, identity-based policies, resource-based policies, fine-grained access control using IAM policy conditions, encryption at rest with AWS KMS, TLS for data in transit, backups, point-in-time recovery, Streams, exports to S3, CloudTrail, CloudWatch, and AWS monitoring integrations.

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

DynamoDB-native controls address important parts of the NoSQL security model. IAM and resource policies govern who can access DynamoDB resources. Fine-grained access control can restrict access to certain items or attributes through IAM policy conditions. Encryption at rest protects table data using AWS KMS. Streams and exports help move data into downstream AWS workflows.

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 DynamoDB-native controls for AWS-managed NoSQL access control, resource permissions, encryption at rest, monitoring, backups, Streams, and exports. Use Ubiq for identity-aware runtime protection of sensitive fields and records across DynamoDB and broader enterprise workflows.

Key Takeaways

• DynamoDB-native security and Ubiq runtime sensitive data protection solve different problems and should be viewed as complementary controls.
• DynamoDB is strong for AWS-native access control, IAM policies, resource-based policies, encryption at rest, monitoring, Streams, exports, and operational resilience.
• Ubiq protects selected sensitive values directly and controls whether an identity or workflow can access those values in cleartext at runtime.
• DynamoDB policies generally govern AWS resource access and API operations. Ubiq helps protect sensitive values before, inside, and beyond DynamoDB.
• Ubiq is especially useful when organizations need to reduce cleartext exposure across applications, service accounts, Lambda functions, APIs, pipelines, BI tools, AI/RAG workflows, exports, and downstream systems.

Control Boundary View

Where DynamoDB Native Security Helps

DynamoDB provides important native controls for securing AWS-managed NoSQL data and API operations.

These controls help teams:

• Authenticate users, applications, and services through AWS IAM
• Authorize DynamoDB API actions through identity-based policies
• Use resource-based policies on tables, indexes, and streams
• Grant cross-account access through resource-based policies
• Apply IAM policy conditions for fine-grained access control to certain items or attributes
• Encrypt all table data at rest using AWS KMS
• Use AWS owned, AWS managed, or customer managed keys where supported
• Protect data in transit using TLS
• Capture item-level changes through DynamoDB Streams or Kinesis Data Streams
• Export table data to S3 for analytics, migration, or downstream processing
• Use backup and point-in-time recovery for operational resilience
• Monitor and audit activity through AWS CloudTrail, CloudWatch, IAM Access Analyzer, and related AWS services

These capabilities are valuable for DynamoDB security.

They help answer questions such as:

• Which IAM users, roles, or services can access this table?
• Which AWS principals can perform specific DynamoDB API actions?
• Which accounts or organizations can access this table, index, or stream?
• Which items or attributes should be accessible through IAM policy conditions?
• Is table data encrypted at rest?
• Which KMS key protects the table?
• Which table changes are streamed downstream?
• Where is table data exported?
• Which DynamoDB operations occurred?

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

However, they are primarily AWS resource, API, and service controls. They govern access, permissions, encryption at rest, monitoring, and data movement within DynamoDB and AWS-controlled paths.

Where DynamoDB Native Security Is Not Designed to Go

DynamoDB-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 DynamoDB API path.

Sensitive values may be accessed, copied, transformed, exported, streamed, logged, embedded, indexed, or consumed by:

• Internal users
• Developers
• Cloud administrators
• Application services
• Lambda functions
• Service accounts
• APIs
• Event-driven workflows
• DynamoDB Streams consumers
• Kinesis consumers
• ETL and ELT pipelines
• BI tools
• Reporting systems
• Data science notebooks
• AI and RAG workflows
• MCP-based tools and agents
• Vector stores
• S3 exports
• Vendor feeds
• Downstream databases
• Replicated datasets
• Temporary development or test environments

DynamoDB can govern access to tables, items, attributes, streams, and API operations. But once sensitive values are returned in cleartext to an authorized caller, streamed downstream, exported to S3, logged, embedded into a vector store, copied into another system, or consumed by a separate workflow, DynamoDB-native controls may no longer be the enforcement point.

That is the architectural gap Ubiq is designed to address.

Comparison Matrix

Key Architectural Differences

AWS Resource Access vs Sensitive Value Protection

DynamoDB-native controls govern access to AWS resources, API operations, items, attributes, streams, and exports.

Ubiq protects selected sensitive values themselves.

This difference is important.

An application, Lambda function, IAM role, or service account may have legitimate access to a DynamoDB table or item 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.

IAM Policy Conditions vs Runtime Cleartext Authorization

DynamoDB supports fine-grained access control through IAM policy conditions. These can restrict access to certain items or attributes for specific IAM principals and API operations.

These controls are useful and should be used where appropriate.

Ubiq adds a separate runtime cleartext authorization model.

With Ubiq, the question is not only:

Is this IAM principal allowed to call this DynamoDB API operation?

The question becomes:

Is this identity, application, Lambda function, 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 used across many workflows, not just one DynamoDB API path.

Encryption at Rest vs Runtime Sensitive Value Protection

DynamoDB encrypts customer data at rest using AWS KMS.

This is a strong control for protecting stored table data.

However, encryption at rest is transparent to authorized DynamoDB access paths. When an authorized caller reads an item, the service returns values according to DynamoDB permissions and application logic.

Ubiq addresses a different question:

Should this caller receive the sensitive value in cleartext?

This distinction matters when the risk is not only storage-layer exposure, but also compromised credentials, broad IAM roles, service account exposure, downstream streams, S3 exports, API responses, logs, BI extracts, or AI workflows.

DynamoDB Boundary vs Downstream Persistence

DynamoDB-native controls are strongest while data remains inside DynamoDB and AWS-controlled access paths.

But sensitive data often moves.

It may be streamed to consumers, exported to S3, 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 DynamoDB table or AWS policy boundary. If protected values are streamed, copied, exported, embedded, indexed, or consumed downstream, they can remain protected unless an authorized runtime path reveals cleartext.

AWS-Native Controls vs Cross-Platform Enforcement

DynamoDB-native security is designed for DynamoDB and AWS-managed workflows.

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 DynamoDB is one part of a larger data environment.

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

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

When to Use Both

DynamoDB-native security and Ubiq are not mutually exclusive.

Organizations should continue using DynamoDB-native controls for:

• AWS IAM authentication and authorization
• Identity-based policies
• Resource-based policies
• Cross-account access control
• IAM policy conditions for fine-grained access
• KMS encryption at rest
• TLS for data in transit
• Backup and point-in-time recovery
• DynamoDB Streams
• Kinesis Data Streams integration
• Export to S3
• CloudTrail and CloudWatch monitoring
• IAM Access Analyzer and policy validation workflows

Ubiq should be considered when organizations also need to:

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

The layered model is simple:

• Use DynamoDB for AWS-native NoSQL access control and managed service security.
• Use Ubiq for runtime sensitive value protection across broader workflows.

How Ubiq Complements DynamoDB

Ubiq complements DynamoDB by protecting sensitive values before, inside, and beyond DynamoDB 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 DynamoDB
• Control cleartext access for users, applications, Lambda functions, service accounts, APIs, and pipelines
• Reduce exposure in event-driven, analytics, BI, and reporting workflows
• Protect sensitive data used by AI, RAG, notebook, model, and agent workflows
• Preserve protection when data is streamed, copied, exported, embedded, indexed, replicated, or consumed downstream
• Maintain separation between DynamoDB access and sensitive value authorization
• Apply consistent protection across DynamoDB and other enterprise data platforms

In this model:

• DynamoDB governs AWS resource access, API permissions, encryption at rest, Streams, exports, monitoring, and operational resilience.
• 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 DynamoDB-native controls and Ubiq together, teams should ask:

• Which sensitive attributes require protection beyond standard DynamoDB access control?
• Which IAM roles, service accounts, applications, Lambda functions, and APIs can access sensitive values today?
• Which workflows receive sensitive data in cleartext?
• Are IAM policy conditions sufficient for the sensitive data exposure risk?
• What happens when sensitive data is streamed, exported, copied, logged, joined, embedded, indexed, or replicated?
• Do BI tools, dashboards, extracts, and reports expose sensitive values outside DynamoDB?
• Do AI, RAG, notebook, MCP, vector store, model training, model inference, or agent workflows access sensitive values?
• Should Lambda functions, service accounts, APIs, or automation workflows receive cleartext, or only protected values?
• How would the organization reduce blast radius if AWS credentials, IAM roles, 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 DynamoDB?

Summary

DynamoDB provides strong native security controls for AWS-managed NoSQL workloads. These controls are important for IAM authorization, resource policies, fine-grained access conditions, encryption at rest, Streams, exports, backups, monitoring, and operational resilience.

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

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

DynamoDB controls AWS resource access and API operations.

Ubiq controls exposure of sensitive values across identities and workflows.

The strongest architecture uses both.