Liquibase Secure vs Liquibase Community

Generates changelogs from natural language requests through the Liquibase MCP server. Output includes rollback logic and database-specific syntax.

Runs governed database deployments from ServiceNow, GitHub, Harness, and Terraform without changing how those tools are used.

Changes are authored in SQL, YAML, JSON, or XML and versioned in Git with application code. Liquibase Secure adds Flows, policy checks, and audit evidence to the same changelogs.

Runs in Jenkins, GitHub Actions, Azure DevOps, GitLab CI, and other CI/CD systems. Liquibase Secure adds policy checks, Flows, and drift detection as pipeline steps.

APIs that apply one database change standard across pipelines, platforms, and teams without rebuilding existing workflows.

Creates changelogs and changesets, runs operations, and applies policy checks inside VS Code.

Runs operations and policy checks against a local database before changes are committed.

Tracks and manages changes to tables, indexes, functions, triggers, stored procedures, and other objects using each database's full feature set.

Flow files define end-to-end pipelines in YAML. Policy checks, rollback scripts, and audit logs are captured as part of each run.

Policy checks, approvals, and evidence collection apply to every change, whether written by a person or an AI assistant.

Records who changed what, where, and when, with history reports, structured logging, and user identity for every change.

Audit trails and policy results from the pipeline are compiled into evidence for SOX, HIPAA, PCI-DSS, SOC 2, DORA, and GDPR audits.

Built-in and custom checks evaluate each change against defined rules and block operations that fail before deployment.

The same policy checks run in the developer's IDE before commit and as CI/CD pipeline steps before deployment.

Scheduled or triggered scans compare deployed schemas to tracked changelogs and flag out-of-band changes. Detected drift can be reconciled by updating code or rolling the change back.

Database credentials are read from HashiCorp Vault, AWS Secrets Manager, or other enterprise secret stores instead of changelogs or property files.

Enforces separation of duties between developers, Ops, and DBAs, supports modern authentication methods, and records each action in the audit trail.

Reports and dashboards cover every change across every database, including deployment health, velocity, and risk trends over time.

Schema changes are standardized and traceable across Snowflake, Databricks, MongoDB, and 65+ database types, with lineage recorded per environment.

Structured logs for every change can be exported to dashboards and reports for audit, compliance, and monitoring.

Failed deployments link to operation history, logs, and execution context. AI-driven analysis summarizes the failure and proposes remediation steps.

DORA metrics and performance health are reported by department, team, pipeline, or database.

Schema drift, policy outcomes, and operational patterns are shown in one dashboard so out-of-process changes are visible early.

Tracks each change from development to test, staging, and production, and shows gaps, failures, and skipped steps.

Compliance evidence reports are generated on request from continuously captured change history, with no manual collection.

Every release ships with a Software Bill of Materials (SBOM). CVE patches are delivered under an SLA.

Liquibase tests each release across supported databases, including regression coverage.

One-step install with certified drivers, extensions, and integrations. Upgrades are guided; patches and hotfixes are SLA-backed.

SLA-backed support with technical account management.

Implementation and best practice services from Liquibase.

Critical vulnerabilities are patched and delivered within 14 days, with proactive notification.