Real-time
Two-way sync
Changes in Amazon RDS or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Database
Amazon RDS to TimescaleDB integration — real-time, two-way sync
Keep Amazon RDS 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.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Amazon RDS and TimescaleDB
Keep Amazon RDS and TimescaleDB synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between Amazon RDS and TimescaleDB continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Use a read replica as the sync source to keep change capture load off the primary instance
- 02 Bi-directional sync between an RDS database and a CRM so application data and sales data stay consistent without custom integration code
- 03 Keep device or asset reference tables bi-directionally in sync between TimescaleDB and an ERP.
- 04 Consolidate metrics from several services into one hypertable to serve a single reporting layer.
Common sync patterns
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both Amazon RDS and TimescaleDB, so each workload runs on the engine that suits it.
What you can sync between Amazon RDS and TimescaleDB
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 RDS objects | TimescaleDB objects | How this pairing syncs | |
|---|---|---|---|
| Schemas Namespaces within a database used to isolate synced tables. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views Read-side projections exposed to outbound syncs. | Views Standard SQL views used to shape or filter data for consumers. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tables The core sync target; rows map to records in connected SaaS systems. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | Tables is specific to Amazon RDS and Hypertables to TimescaleDB — each maps to any object or custom field on the other side. | |
| Columns Field-level mapping targets, typed per the underlying engine. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | Columns is specific to Amazon RDS and Chunks to TimescaleDB — each maps to any object or custom field on the other side. | |
| Primary and Unique Keys Match keys for idempotent upserts. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | Primary and Unique Keys is specific to Amazon RDS and Continuous Aggregates to TimescaleDB — each maps to any object or custom field on the other side. | |
| Read Replicas Low-impact read endpoints often used as the source side of a sync. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | Read Replicas is specific to Amazon RDS and Regular PostgreSQL Tables to TimescaleDB — each maps to any object or custom field on the other side. |
How changes propagate between Amazon RDS and TimescaleDB
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
Amazon RDS TimescaleDB Sub-second propagation
DetectionChanges in Amazon RDS are captured at the source via change data capture — no polling loop against its API. Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC.
DeliveryEach detected change is applied to TimescaleDB as a row-level write, with types converted between the two schemas.
TimescaleDB Amazon RDS Sub-second propagation
DetectionChanges in TimescaleDB are captured at the source via change data capture — no polling loop against its API. Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must.
DeliveryEach detected change is applied to Amazon RDS as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Amazon RDS: No API rate limits; throughput depends on instance class, storage IOPS, and connection limits.
- TimescaleDB: No API rate limits; throughput is bounded by database resources and connection limits.
What ships with Amazon RDS ⇄ TimescaleDB
Connect Amazon RDS and TimescaleDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon RDS–TimescaleDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Amazon RDS or TimescaleDB data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single Amazon RDS or TimescaleDB record.
Observability
Monitoring
Track your Amazon RDS ⇄ TimescaleDB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Amazon RDS and TimescaleDB.
How the Amazon RDS and TimescaleDB connectors work
Amazon RDS
- Integration surface
- SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle)
- Authentication
- Database credentials over SSL/TLS, or IAM database authentication on supported engines
- Change detection
- Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC; enabled through RDS parameter groups, with polling as a fallback
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput depends on instance class, storage IOPS, and connection limits
TimescaleDB
- Integration surface
- SQL wire protocol (PostgreSQL)
- Authentication
- Database credentials
- Change detection
- 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
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by database resources and connection limits.
How it works
How to connect Amazon RDS to TimescaleDB — three steps, no code
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.
- 01
Connect your apps
Authenticate Amazon RDS 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.
Amazon RDS
connected
TimescaleDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Amazon RDS 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.
objects · Amazon RDS ⇄ TimescaleDBCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Amazon RDS TimescaleDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Amazon RDS and TimescaleDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Amazon RDS and TimescaleDB: authenticate both systems, choose the objects to sync (such as Amazon RDS's Schemas and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Amazon RDS side: Views, Columns, Primary and Unique Keys, Read Replicas, plus custom fields where Amazon RDS exposes them. On the TimescaleDB side: Schemas, Hypertables, Chunks, Continuous Aggregates. Stacksync auto-detects both schemas and converts types between the two systems.
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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.
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Common patterns for Amazon RDS and TimescaleDB: Shared reference data between services; Regional or environment copies; Cross-engine sync. Services that own separate databases stay consistent on the records they share, without a custom replication layer.
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Amazon RDS: SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle). Authentication: Database credentials over SSL/TLS, or IAM database authentication on supported engines. TimescaleDB: SQL wire protocol (PostgreSQL). Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
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Amazon RDS: RDS is a managed hosting layer, not a separate API: clients connect with standard engine drivers at the instance endpoint. TimescaleDB: TimescaleDB is packaged as a PostgreSQL extension, so standard Postgres drivers and SQL tooling work unchanged. Stacksync's field mapping accounts for these differences between Amazon RDS and TimescaleDB without custom code.
SECURITY
Security teams trust Stacksync
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Related integrations
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