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Data warehouse ⇄ Database

AWS S3 to Citus integration — real-time, two-way sync

Keep AWS S3 and Citus in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect AWS S3 and Citus

Connect Citus 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 Citus'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 Citus where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Citus sync into AWS S3 in real time, and result tables in AWS S3 sync back into Citus, with schema and type mapping between the two systems handled for you.

Common use cases

  • Archive change history from ongoing syncs as timestamped files for audit and replay.
  • Ingest partner or vendor file drops (CSV, JSON, Parquet) from a bucket into a database or CRM as records.
  • Use a Citus cluster as the scalable operational store behind a customer-facing app while syncing summaries back to internal tools.
  • Consolidate per-tenant rows from distributed tables into per-customer reporting databases.

Offload heavy reads

Point analytical queries at the synced copy in AWS S3 and keep Citus focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from Citus land in AWS S3 as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in AWS S3 sync into Citus, where whatever reads from that database gets them without querying the warehouse.

What you can sync between AWS S3 and Citus

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 Citus objects
Event Notifications Notifications on object creation or deletion that trigger incremental processing. Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets.
Access Points Scoped network endpoints used to grant a sync narrow access to a bucket. Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables.
Multipart Uploads The mechanism used to write large export files reliably. Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables.
Buckets Top-level containers a sync targets; region and policy are set at this level. Schemas Standard Postgres namespaces used to scope what a sync user can read and write.
Objects The stored files (CSV, JSON, Parquet); syncs read them as datasets or write exports into them. Views Curated projections over distributed data, often used as read-only sync sources.
Prefixes Key-name paths used to partition synced datasets, since S3 has no real directories. Sequences Key generators that matter when external writes must not collide with application inserts.
What ships with AWS S3 ⇄ Citus

Connect AWS S3 and Citus for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS S3–Citus connection.

Real-time

Two-way sync

Changes in AWS S3 or Citus instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS S3 or Citus 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 Citus record.

Observability

Monitoring

Track your AWS S3 ⇄ Citus 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 Citus.

How the AWS S3 and Citus 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

Citus

Integration surface
PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node
Authentication
Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options)
Change detection
PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres
Capabilities
read · write · CDC
How it works

How to connect AWS S3 to Citus — 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.

  1. 01

    Connect your apps

    Authenticate AWS S3 and Citus with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    AWS S3 connected
    Citus connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS S3 and Citus 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · AWS S3 ⇄ Citus
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    AWS S3 Citus
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS S3 and Citus integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for AWS S3 and Citus.

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