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Database ⇄ Data warehouse

Citus to Firebolt integration — real-time, two-way sync

Keep Citus and Firebolt 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

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Why teams connect Citus and Firebolt

Connect Citus and Firebolt 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 Firebolt, 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 Firebolt in real time, and result tables in Firebolt sync back into Citus, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Sync aggregated results from Firebolt back to operational tools that need computed metrics (reverse ETL).
  • 02 Sync CRM objects into Firebolt so customer-facing dashboards reflect recent pipeline changes.
  • 03 Sync high-volume event or tenant data from a Citus cluster into a warehouse for cross-tenant analytics.
  • 04 Write CRM or billing records into reference tables so distributed queries can join operational context locally on every node.

Common sync patterns

Offload heavy reads

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

Operational data in the warehouse, minus the pipeline

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

Serve warehouse results at database speed

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

What you can sync between Citus and Firebolt

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.

Citus objects Firebolt objects How this pairing syncs
Views Curated projections over distributed data, often used as read-only sync sources. Views Curated query surfaces commonly used as sources for reverse ETL. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. Databases Logical containers holding the tables a sync targets. Reference tables is specific to Citus and Databases to Firebolt — each maps to any object or custom field on the other side.
Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. Tables Managed columnar tables written with SQL; the main sync destination. Local tables is specific to Citus and Tables to Firebolt — each maps to any object or custom field on the other side.
Schemas Standard Postgres namespaces used to scope what a sync user can read and write. External tables References to files in object storage used to stage bulk loads. Schemas is specific to Citus and External tables to Firebolt — each maps to any object or custom field on the other side.
Sequences Key generators that matter when external writes must not collide with application inserts. Aggregating indexes Precomputed rollups maintained at write time; incremental loads update them automatically. Sequences is specific to Citus and Aggregating indexes to Firebolt — each maps to any object or custom field on the other side.
Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. Engines Compute resources that must be running for a sync to read or write. Distributed tables is specific to Citus and Engines to Firebolt — each maps to any object or custom field on the other side.

How changes propagate between Citus and Firebolt

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.

Citus Firebolt Sub-second propagation

DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.

DeliveryEach detected change is applied to Firebolt as a row-level write, with types converted between the two schemas.

Firebolt Citus Interval-based propagation

DetectionStacksync polls Firebolt for changes on an incremental schedule, reading only records changed since the previous pass. Polling.

DeliveryEach detected change is applied to Citus as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Firebolt: No fixed request quota; throughput depends on the engine size attached to the workload.
What ships with Citus ⇄ Firebolt

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Citus or Firebolt 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 Citus or Firebolt record.

Observability

Monitoring

Track your Citus ⇄ Firebolt sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Citus and Firebolt.

How the Citus and Firebolt connectors work

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

Firebolt

Integration surface
SQL over a REST API, with JDBC, Python, and Node.js SDKs
Authentication
Service account credentials (client ID and secret) exchanged for OAuth 2.0 tokens
Change detection
Polling; Firebolt is an analytics destination and does not expose a change feed
Capabilities
read · write
Rate limits
No fixed request quota; throughput depends on the engine size attached to the workload
How it works

How to connect Citus to Firebolt — 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 Citus and Firebolt 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
    Citus connected
    Firebolt connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Citus and Firebolt 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 · Citus ⇄ Firebolt
    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
    Citus Firebolt
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Citus and Firebolt integration FAQ

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.

Learn more about security
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:

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 369 integrations available for Citus and Firebolt.

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