Real-time
Two-way sync
Changes in AWS S3 or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
AWS S3 to TimescaleDB integration — real-time, two-way sync
Keep AWS S3 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 Matillion
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Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect AWS S3 and TimescaleDB
Connect TimescaleDB and AWS S3 with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.
Operational databases and analytical warehouses want the same data at different moments. Analysts want TimescaleDB's rows in AWS S3, 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 AWS S3 in real time, and result tables in AWS S3 sync back into TimescaleDB, with schema and type mapping between the two systems handled for you.
Common use cases
- Ingest partner or vendor file drops (CSV, JSON, Parquet) from a bucket into a database or CRM as records.
- Export synced operational data to S3 as files feeding a data lake or downstream batch jobs.
- Consolidate metrics from several services into one hypertable to serve a single reporting layer.
- Sync product or IoT telemetry stored in TimescaleDB into a CRM so account teams see usage metrics next to the customer record.
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Offload heavy reads
Point analytical queries at the synced copy in AWS S3 and keep TimescaleDB focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from TimescaleDB land in AWS S3 as they change, replacing hand-built CDC and batch extract jobs.
What you can sync between AWS S3 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.
| AWS S3 objects | TimescaleDB objects | |
|---|---|---|
| Multipart Uploads The mechanism used to write large export files reliably. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | |
| Buckets Top-level containers a sync targets; region and policy are set at this level. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | |
| Objects The stored files (CSV, JSON, Parquet); syncs read them as datasets or write exports into them. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | |
| Prefixes Key-name paths used to partition synced datasets, since S3 has no real directories. | Views Standard SQL views used to shape or filter data for consumers. | |
| Object Metadata System and user-defined metadata read alongside object contents. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | |
| Object Versions Prior copies retained when versioning is enabled, relevant for reprocessing. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. |
What ships with AWS S3 ⇄ TimescaleDB
Connect AWS S3 and TimescaleDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS S3–TimescaleDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS S3 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 AWS S3 or TimescaleDB record.
Observability
Monitoring
Track your AWS S3 ⇄ TimescaleDB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between AWS S3 and TimescaleDB.
How the AWS S3 and TimescaleDB connectors work
AWS S3
- Integration surface
- REST API (the S3 API), accessed directly or through AWS SDKs
- Authentication
- AWS IAM credentials with SigV4 signing; commonly a role scoped to specific buckets and prefixes
- Change detection
- S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge; list-based polling as a fallback
- Capabilities
- read · write · webhooks
- Rate limits
- Request throughput scales per prefix; sustained high-volume workloads should spread keys across prefixes
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 AWS S3 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 AWS S3 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.
AWS S3
connected
TimescaleDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS S3 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 · AWS S3 ⇄ 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.
AWS S3 TimescaleDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS S3 and TimescaleDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between AWS S3 and TimescaleDB: authenticate both systems, choose the objects to sync (such as AWS S3's Multipart Uploads and Buckets), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed AWS S3 and TimescaleDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS S3–TimescaleDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both AWS S3 and TimescaleDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on AWS S3: S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge; list-based polling as a fallback. 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.
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On the AWS S3 side: Event Notifications, Access Points, Multipart Uploads, Buckets, plus custom fields where AWS S3 exposes them. On the TimescaleDB side: Chunks, Continuous Aggregates, Regular PostgreSQL Tables, Views. 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.
SECURITY
Security teams love 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
CSA STAR
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
Every pair below is a real-time, two-way sync. Search all 386 integrations available for AWS S3 and TimescaleDB.
Popular · 8 of 386
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AWS S3 ⇄ SQL Server -
AWS S3 ⇄ Postgres Heroku -
AWS S3 ⇄ Airtable -
AWS S3 ⇄ AWS Aurora MySQL -
TimescaleDB ⇄ Vertica -
TimescaleDB ⇄ Yellowbrick -
TimescaleDB ⇄ Snowflake -
TimescaleDB ⇄ BigQuery
No integrations match .
