Connect Amazon S3 and
PostgreSQL with AI

Automate the flow between your data lake and relational database. Stop manually writing ETL scripts, parsing CSV files, or building custom loaders to move data from S3 buckets into PostgreSQL tables.

No code required
Live in minutes
SOC 2 Type II

What you can automate today

Redbird gives your team ready-to-run workflows — just connect your accounts and go.

Auto-load new CSV and JSON files from S3 into PostgreSQL tables

Automatically detect new files landing in S3 buckets and load them into the correct PostgreSQL tables. Redbird maps columns, handles schema evolution, and transforms data types without custom scripts.

Export PostgreSQL query results to S3 for downstream analytics processing

Run scheduled or triggered queries against PostgreSQL and write results to S3 as partitioned Parquet or CSV files. Perfect for feeding data warehouses, ML pipelines, or archival workflows.

Sync S3 data lake partitions into PostgreSQL staging tables nightly

Automatically load the latest partition from your S3 data lake into PostgreSQL staging tables every night. Enables analysts to query fresh data with SQL tools without touching infrastructure.

Backup PostgreSQL tables to S3 on a schedule with versioning

Export full or incremental PostgreSQL table snapshots to S3 with automatic timestamping and versioning. Keep cost-effective backups separate from your primary database infrastructure.

Load ML model outputs from S3 into PostgreSQL for application use

When ML pipelines write prediction files to S3, automatically parse and insert results into PostgreSQL tables. Makes model outputs immediately queryable by your application backend.

Enrich S3 event logs with PostgreSQL reference data before archiving

As raw event files arrive in S3, join them with customer or product data from PostgreSQL, then write enriched files back to S3. Builds analysis-ready datasets without Spark jobs.

Live in four steps

No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.

01

Connect your accounts

Authorize Amazon S3 and PostgreSQL with OAuth or API credentials. Redbird never stores your data — it just passes through.

02

Describe what you want

Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.

03

Review and activate

Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.

04

Let it run — and iterate

Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.

Built for data-driven teams

Redbird understands both S3 object structures and PostgreSQL schemas, so it can intelligently map files to tables without brittle configuration.

AI that reads your S3 files and PostgreSQL schemas

Redbird automatically infers structure from CSV, JSON, and Parquet files in S3, then maps columns to PostgreSQL table schemas. It handles type conversions, null values, and nested JSON fields. When schemas change, Redbird detects differences and adapts mappings, so your pipelines don't break when a new column appears in your data lake.

Automatic column mapping
Schema drift detection
Type inference & conversion
Nested JSON flattening
10×

faster than writing custom Python ETL scripts for S3-to-PostgreSQL loads

No pandas, boto3, or psycopg2 scripts to maintain and debug

Auto-generated reports

Redbird can pull from Amazon S3 and PostgreSQL simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.

Trigger-based alerts

Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Amazon S3 or PostgreSQL.

Enterprise-grade security

SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.

Bidirectional sync

Push data from Amazon S3 into PostgreSQL, or from PostgreSQL back into Amazon S3. Resolve conflicts with configurable merge rules.

Full audit trail

Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.

Triggers & actions for every team

Start automations from new files in S3 buckets or database events in PostgreSQL, and take action in either system.

Amazon S3
Triggers & Actions
Trigger

New file added to bucket

Trigger when a new object is uploaded to a specific S3 bucket or prefix path.

Trigger

File modified or overwritten

Detect when an existing S3 object is updated or replaced with a new version.

Trigger

Scheduled bucket scan

Run on a schedule to check for new or changed files matching specific patterns.

Action

Read and parse file contents

Fetch a file from S3 and parse it as CSV, JSON, Parquet, or other structured formats.

Action

Write data to bucket

Upload new files or overwrite existing objects in an S3 bucket with specified content.

Action

Archive or move objects

Copy or move files between S3 buckets or prefixes after processing.

PostgreSQL
Triggers & Actions
Trigger

New rows inserted into table

Trigger when new records are added to a specified PostgreSQL table.

Trigger

Table row updated

Detect when existing rows in a table are modified based on timestamp or trigger conditions.

Trigger

Scheduled query execution

Run a SQL query on a schedule and use results to trigger downstream actions.

Action

Insert rows into table

Load new data into a PostgreSQL table with automatic schema matching and type conversion.

Action

Update existing records

Modify rows in a table based on matching keys or conditions from external data.

Action

Run custom SQL query

Execute arbitrary SQL commands for transformations, aggregations, or data cleanup.

Amazon S3
+
PostgreSQL

Ready to connect your stack?

Stop building one-off scripts to move data between S3 and PostgreSQL. Redbird automates the entire pipeline with AI that adapts to your schemas.

Get started → Book a demo