Two-way sync
Changes in Amazon Redshift or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon Redshift and TimescaleDB 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 TimescaleDB'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 TimescaleDB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in TimescaleDB sync into Amazon Redshift in real time, and result tables in Amazon Redshift sync back into TimescaleDB, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Amazon Redshift and keep TimescaleDB focused on its operational workload.
Rows from TimescaleDB land in Amazon Redshift as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Amazon Redshift sync into TimescaleDB, where whatever reads from that database gets them without querying the warehouse.
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 | TimescaleDB objects | |
|---|---|---|
| External Tables (Spectrum) S3-backed tables queryable through Redshift, readable in syncs. | Views Standard SQL views used to shape or filter data for consumers. | |
| Stored Procedures SQL procedures sometimes invoked around load steps. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | |
| Users and Groups Principals used to grant a sync connection scoped access. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | |
| Databases Top-level containers within a cluster or serverless workgroup. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | |
| Schemas Namespaces used to organize synced tables and control grants. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | |
| Tables Columnar tables used as sync destinations for SaaS and database data. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Redshift–TimescaleDB connection.
Changes in Amazon Redshift or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon Redshift or TimescaleDB 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 TimescaleDB record.
Track your Amazon Redshift ⇄ TimescaleDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon Redshift and TimescaleDB.
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 TimescaleDB 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 TimescaleDB 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 TimescaleDB: authenticate both systems, choose the objects to sync (such as Amazon Redshift's External Tables (Spectrum) and Stored Procedures), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Amazon Redshift: Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers. On TimescaleDB: Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Amazon Redshift side: Views, Materialized Views, External Tables (Spectrum), Stored Procedures, plus custom fields where Amazon Redshift exposes them. On the TimescaleDB side: Regular PostgreSQL Tables, Views, Schemas, Hypertables. 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 TimescaleDB: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Amazon Redshift and keep TimescaleDB focused on its operational workload.
Amazon Redshift: SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS. Authentication: Database credentials or IAM-based authentication. TimescaleDB: SQL wire protocol (PostgreSQL). Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
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 TimescaleDB.