Two-way sync
Changes in Amazon Redshift or DuckDB instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon Redshift and DuckDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want DuckDB's rows in Amazon Redshift, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in DuckDB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in DuckDB sync into Amazon Redshift in real time, and result tables in Amazon Redshift sync back into DuckDB, with schema and type mapping between the two systems handled for you.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Point analytical queries at the synced copy in Amazon Redshift and keep DuckDB focused on its operational workload.
Rows from DuckDB land in Amazon Redshift as they change, replacing hand-built CDC and batch extract jobs.
Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.
| Amazon Redshift objects | DuckDB objects | |
|---|---|---|
| Users and Groups Principals used to grant a sync connection scoped access. | Views SQL views used to shape or filter data for downstream consumers. | |
| Databases Top-level containers within a cluster or serverless workgroup. | External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | |
| Schemas Namespaces used to organize synced tables and control grants. | Attached databases Additional database files or external systems attached into one session for cross-source queries. | |
| Tables Columnar tables used as sync destinations for SaaS and database data. | Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | |
| Views SQL views readable as modeled sources for reverse syncs. | Schemas Namespaces within a database used to organize tables in sync outputs. | |
| Materialized Views Precomputed results that downstream syncs can read for performance. | Tables Columnar tables created via SQL; the destination for materialized sync data. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Redshift–DuckDB connection.
Changes in Amazon Redshift or DuckDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon Redshift or DuckDB data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon Redshift or DuckDB record.
Track your Amazon Redshift ⇄ DuckDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon Redshift and DuckDB.
Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.
Authenticate Amazon Redshift and DuckDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Amazon Redshift and DuckDB objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Amazon Redshift and DuckDB: authenticate both systems, choose the objects to sync (such as Amazon Redshift's Users and Groups and Databases), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Amazon Redshift side: Views, Materialized Views, External Tables (Spectrum), Stored Procedures, plus custom fields where Amazon Redshift exposes them. On the DuckDB side: Attached databases, Database files, Schemas, Tables. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for Amazon Redshift and DuckDB: Fresh analytics without loading windows; Offload heavy reads; Operational data in the warehouse, minus the pipeline. Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Amazon Redshift: SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS. Authentication: Database credentials or IAM-based authentication. DuckDB: In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default. Authentication: None built in; access control is file-system level (MotherDuck adds token auth for its hosted service). Stacksync manages authentication, retries, and rate limits on both sides.
Amazon Redshift: Its SQL dialect derives from PostgreSQL, so standard Postgres drivers connect, though not all Postgres features exist. DuckDB: Concurrency is single-writer: one process holds write access to a database file at a time, which shapes how sync jobs schedule writes. Stacksync's field mapping accounts for these differences between Amazon Redshift and DuckDB without custom code.
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Amazon Redshift and DuckDB.