Redbird AI automates the orchestration between your Databricks lakehouse and GCS buckets. Stop manually syncing processed datasets, tracking ML artifacts across storage layers, or writing custom scripts to move data between your compute and storage environments.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically export completed Databricks Delta tables to Google Cloud Storage buckets configured for long-term archival. Redbird monitors job completion, partitions output by date, and applies appropriate storage classes based on access patterns.
Start ETL pipelines and transformation workflows in Databricks the moment new files appear in designated GCS buckets. Redbird watches for file creation events, validates schemas, and initiates the appropriate Databricks job with context-aware parameters.
Export model artifacts, feature stores, and training datasets from Databricks to GCS buckets optimized for serving infrastructure. Redbird handles version tracking, metadata preservation, and cross-region replication configuration automatically.
Ingest streaming data files from GCS into Databricks Delta tables with intelligent schema detection and evolution. Redbird monitors bucket prefixes, handles format variations, and merges new data while maintaining table history and ACID compliance.
Monitor compute spending in Databricks relative to data volume in GCS and notify teams when processing costs become inefficient. Redbird analyzes cluster utilization patterns, compares against storage growth, and suggests optimization opportunities.
Automatically export Databricks notebook execution results, query outputs, and data lineage information to structured GCS paths with timestamp and user metadata. Redbird ensures regulatory compliance by maintaining immutable audit trails with appropriate retention policies.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Databricks and Google Cloud Storage 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 understands both Databricks workspace structures and GCS bucket hierarchies — from Delta table schemas and job clusters to object lifecycle policies and storage classes.
Redbird natively interprets Databricks Delta table metadata, catalog structures, and job orchestration patterns alongside GCS bucket configurations, object naming conventions, and access control policies. Our AI maps between Databricks' ACID-compliant table formats and GCS object paths, handling partition schemes, compression formats, and serialization automatically. Whether you're moving Parquet files, MLflow artifacts, or streaming checkpoint data, Redbird maintains data integrity across compute and storage layers without custom transformation code.
faster than writing and maintaining custom Databricks-to-GCS connector scripts
Redbird can pull from Databricks and Google Cloud Storage 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 Databricks or Google Cloud Storage.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Databricks into Google Cloud Storage, or from Google Cloud Storage back into Databricks. 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 job completions in Databricks or file events in Google Cloud Storage — Redbird connects both sides of your lakehouse architecture.
Fires when a Databricks job finishes running, including job metadata and output table references.
Triggers when a Delta Lake table receives new data or schema changes in the Unity Catalog.
Detects compute cluster lifecycle events for cost tracking and resource optimization workflows.
Write data to Databricks Delta tables with automatic schema merging and partition management.
Execute Databricks workflows and notebooks with dynamic input values from upstream events.
Run SQL analytics queries against Databricks SQL endpoints and retrieve structured results.
Fires immediately when new objects appear in specified GCS bucket paths or prefixes.
Detects updates to GCS object tags, storage class transitions, or custom metadata fields.
Triggers when storage volume crosses defined limits, enabling capacity planning workflows.
Write objects to GCS with specified storage class, metadata, and versioning configuration.
Transfer files across GCS locations for replication, archival, or multi-region distribution.
Modify retention rules and storage class transitions based on data access patterns and age.
Join data teams using Redbird to sync Databricks and Google Cloud Storage without writing connector code. Get your lakehouse and object storage working together in minutes, not sprints.