Redbird AI syncs your dbt transformation models with Oracle DB enterprise data—automatically. Stop writing custom Python scripts to extract Oracle tables, manually tracking schema changes, or building one-off pipelines to move data between your source systems and analytics layer.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Trigger dbt runs whenever critical Oracle tables are modified. Redbird detects schema changes, new partitions, or data refreshes in Oracle and kicks off the appropriate dbt jobs to keep your analytics warehouse synchronized with production data.
When dbt data quality tests fail, automatically write failure records to Oracle audit tables for compliance tracking. Redbird captures test metadata, failure reasons, and row-level details, creating a centralized data quality log in your source system that finance and compliance teams can query.
Automatically pull updated records from Oracle Financials, HR, or Supply Chain modules and land them in your data warehouse staging layer. Redbird handles incremental extraction logic, tracks high-water marks, and prepares source data for dbt models without manual intervention.
Push aggregated metrics, calculated KPIs, or ML scores from dbt models back into Oracle tables that power operational applications. Redbird maps dbt model outputs to Oracle schemas, handles type conversions, and manages upsert logic so transformed data becomes actionable in production systems.
Detect when Oracle table structures change—new columns, type modifications, or dropped fields—and automatically update dbt source YAML files. Redbird compares live Oracle schemas against dbt source definitions and creates pull requests with updated configurations to prevent pipeline breaks.
Store complete dbt run history, model lineage graphs, and data transformation logs in Oracle tables for audit and regulatory requirements. Redbird captures every dbt execution, translates JSON artifacts into relational structures, and maintains a queryable compliance archive in your enterprise database.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize dbt and Oracle DB with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird AI understands both dbt's semantic layer and Oracle's enterprise data structures—so you can connect modern analytics workflows with legacy source systems intelligently.
Redbird automatically maps Oracle table schemas to dbt source definitions, understanding complex Oracle data types like CLOB, TIMESTAMP WITH TIME ZONE, and nested object tables. It translates dbt model outputs back into Oracle-compatible structures, handling partitioning schemes, indexing strategies, and constraint validation. When Oracle schemas evolve, Redbird identifies impacted dbt models and suggests configuration updates, keeping your transformation layer synchronized with production databases without manual schema reconciliation.
faster than building custom Oracle-to-warehouse extraction scripts
Redbird can pull from dbt and Oracle DB simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either dbt or Oracle DB.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from dbt into Oracle DB, or from Oracle DB back into dbt. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start automations from dbt test results, Oracle table changes, or any event across your data stack.
Fires when any dbt model finishes building, whether successful or failed.
Triggers when data quality tests detect anomalies or constraint violations.
Activates when source data hasn't been updated within expected timeframes.
Execute targeted dbt runs with custom selectors and parameters.
Modify source configurations and create pull requests with changes.
Rebuild and publish dbt docs site with latest model metadata.
Detects when tables receive new records or undergo bulk updates.
Fires when DDL operations alter table structures, add columns, or change types.
Triggers when new partitions are created in time-series or range-partitioned tables.
Insert or upsert rows into Oracle with type validation and constraint handling.
Call PL/SQL procedures with parameters and capture return values.
Pull full or incremental data from Oracle into warehouse landing zones.
Sync dbt with Oracle DB in minutes. Redbird AI handles the complexity of connecting modern transformation workflows with enterprise source systems—so your team can focus on building models, not maintaining infrastructure.