When engineering teams scale a CockroachDB cluster across multiple regions, application availability goes up. But for security teams, visibility often drops.
Modern distributed databases make data resilient, fast, and globally accessible. However, as tables multiply and schemas evolve, tracking sensitive records and complex user access paths becomes an operational hurdle.
Today, Matters.AI and CockroachDB are partnering to eliminate that trade-off.
This strategic partnership combines CockroachDB’s resilient distributed database infrastructure with Matters.AI’s automated data security intelligence. Together, we enable enterprise security teams to maintain complete visibility into sensitive records, identity privileges, and compliance posture as their database footprint scales.
In this post, we explore how this partnership:
- Solves distributed visibility challenges by discovering sensitive records down to the column.
- Maps user access by connecting database roles directly to regulated records.
- Maintains strict data privacy by processing content locally through a hybrid architecture.
The Distributed Data Visibility Challenge
Monolithic database deployments made tracking sensitive data relatively predictable. Modern distributed environments, by contrast, feature dynamic schemas, multi-region replication, and complex database role hierarchies that evolve rapidly alongside engineering workflows.
Traditional security monitoring solutions offer infrastructure-level status, confirming that a database cluster exists and is running. However, they lack granular insight into the sensitive records housed within individual tables and columns.
This creates immediate operational gaps for security and compliance leaders:
- Schema Drift: Sensitive data ends up in unauthorized or unmonitored tables during fast-paced production updates.
- Over-Privileged Access: Grant lists grow complex, making it difficult to verify which roles can actually reach regulated records.
- Residency Risks: Multi-region replication creates potential cross-border regulatory violations without security team oversight.
By bringing automated data security intelligence directly to CockroachDB environments, security teams can safely support database modernization without sacrificing governance.
Better Together: Infrastructure Resilience Meets Data Security Intelligence
Rather than managing database scaling and security visibility as isolated initiatives, this partnership brings them together into a unified operational workflow.
1. Sensitive Data Discovery Down to the Column
Matters.AI automatically scans CockroachDB databases, tables, and columns to classify sensitive data with high precision. Coverage includes 38 PII detectors, 8 regulatory jurisdictions, PCI primary account numbers, PHI health identifiers, and API secrets embedded inside freeform text columns.
Findings are structured across three layers:
- Database Level: High-level inventory of databases containing regulated data.
- Table Level: Breakdown of sensitive tables, total row counts, and data type combinations.
- Column Level: Precise identification of specific columns holding sensitive information, paired with regulatory relevance.
2. Identity and Access Reachability
Identifying sensitive data is only useful if you know who can touch it. Matters.AI correlates CockroachDB users, roles, and permissions directly against classified sensitive records.
Instead of wading through flat permission lists, security teams get immediate, actionable context:
Example Finding:
“14 specific database users hold privileges allowing them to read tables containing active PCI card data”.
3. Exposure Detection and Compliance Guardrails
Matters.AI continuously monitors CockroachDB environments for over-privileged roles, excessive access paths, and cross-border data residency violations.
Every alert isolates the exact database, table, role, and sensitive data type involved, offering step-by-step remediation mapped directly to frameworks like PCI DSS, HIPAA, GDPR, DPDP, ISO 27001, and SOC 2.
Data Privacy by Design: The Hybrid Dataplane
Security tools should never introduce new data exposure risks. To preserve strict data privacy and regulatory compliance, Matters.AI operates on a hybrid dataplane architecture.
| Component | Location | Function |
| Control Plane | Matters.AI Cloud | Manages policy catalogs, detection rules, compliance dashboards, and remediation workflows. |
| Dataplane | Customer Infrastructure | Executes scans, classifies PII, and evaluates security risks locally under customer IAM. |
The Zero-Data-Leakage Guarantee:
All discovery and classification processing happens locally inside your environment. Raw database records and sampled values never leave your network. Only high-level security findings and operational metadata move upstream to the control plane.
Example Upstream Metadata: users.phone contains Indian mobile numbers, 214,003 rows, PII, Reachability: Critical
What Security Leaders Can Now Answer
Through this joint solution, CISOs, Heads of Security, and DevSecOps teams can answer critical operational questions across their distributed database footprint instantly:
- What sensitive data exists? Full visibility into PII, PHI, PCI, and embedded secrets across all CockroachDB tables.
- Who can reach it? Precise mapping between database roles and actual access to regulated records.
- Where is it exposed? Automated detection of overbroad permissions and cross-border residency risks.
- Which regulations apply? Continuous mapping of database findings to global compliance frameworks.
- What needs attention first? Prioritized remediation workflows based on real data risk.
Supporting Modern Distributed Infrastructure
Infrastructure scale and data security visibility must grow together. CockroachDB gives engineering teams the multi-region resilience and horizontal performance required to run modern applications. Matters.AI gives security teams the clarity required to understand, monitor, and protect the data inside those environments.
To see the joint capability in action or to schedule a technical walkthrough, “Talk to us“.