Automate the flow between your cloud data lake and enterprise database. Stop manually downloading CSVs from S3, writing custom BULK INSERT scripts, and building brittle ETL jobs to keep your SQL Server tables in sync with cloud storage.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
When new CSV, Parquet, or JSON files land in S3 buckets, Redbird detects the schema and loads them into SQL Server staging tables. Map source files to target tables once, then let the automation handle schema validation, data type conversion, and incremental loads without writing SQL scripts.
Run scheduled SQL queries and push results to S3 in your preferred format—compressed CSV, Parquet, or JSON. Perfect for archiving transactional data, creating snapshots for compliance, or staging data for consumption by Spark, Athena, or other cloud analytics tools.
Keep reference data, product catalogs, and dimension tables synchronized between your S3 data lake and SQL Server. Redbird monitors S3 for updated lookup tables and merges changes into SQL Server, ensuring your transactional systems have access to current dimensional data without manual imports.
Automatically transfer SQL Server database backups and transaction logs to S3 for off-site storage. Set retention policies, organize backups by database and timestamp, and ensure your enterprise data has cloud-based disaster recovery without scripting custom upload jobs.
When third-party vendors drop data files into shared S3 buckets, Redbird validates the schema against your SQL Server tables and loads clean records into fact tables. Handle data quality issues with alerts, route bad records to quarantine tables, and maintain audit trails of every load.
Push materialized views, aggregated reports, or denormalized datasets from SQL Server to S3 on a schedule. Make enterprise database insights available to cloud-based BI tools, machine learning pipelines, and cross-functional teams who need data in cloud storage formats.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Amazon S3 and SQL Server 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 S3 object structures and SQL Server table schemas, so you can connect cloud storage to enterprise databases without building custom ETL infrastructure.
Redbird automatically infers schemas from S3 files—whether CSV, JSON, Parquet, or Avro—and maps them to SQL Server data types, handling varchar lengths, numeric precision, and datetime formats. It detects primary keys, understands partitioning patterns in S3 prefixes, and generates the appropriate MERGE, INSERT, or BULK LOAD statements based on your table structure. No more manually writing column mappings or dealing with data type mismatches between cloud files and database tables.
faster than building custom S3-to-SQL ETL scripts
Redbird can pull from Amazon S3 and SQL Server 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 Amazon S3 or SQL Server.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Amazon S3 into SQL Server, or from SQL Server back into Amazon S3. 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 workflows from any event in S3 or SQL Server—new files uploaded, tables updated, queries completed, or scheduled intervals.
Trigger when any file or files matching a prefix pattern are added to an S3 bucket.
Detect when existing objects are updated or overwritten in a particular S3 path.
Run on a schedule to check for new or changed files matching your criteria.
Parse CSV, JSON, Parquet, or other structured formats from S3 objects.
Write files to S3 with custom naming, prefixes, and format options.
Relocate S3 objects between prefixes or buckets after processing.
Trigger when data changes in specific SQL Server tables or views.
Run a SELECT query on a schedule and use results to trigger workflows.
Detect when specific stored procedures finish execution in SQL Server.
Write data into SQL Server tables with MERGE logic for upserts.
Call SQL Server stored procedures with parameters from your workflow.
Execute SELECT, UPDATE, or DELETE statements against your database.
Stop building and maintaining custom ETL scripts between S3 and SQL Server. Redbird connects your cloud storage to enterprise databases with AI-powered automation that adapts to your schemas.