Skip to content
Database

Citus to SQL Server integration — real-time, two-way sync

Keep Citus and SQL Server 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
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Citus and SQL Server

Keep Citus and SQL Server 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 Citus and SQL Server 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 Consolidate per-tenant rows from distributed tables into per-customer reporting databases.
  • 02 Sync high-volume event or tenant data from a Citus cluster into a warehouse for cross-tenant analytics.
  • 03 Feed a cloud warehouse from SQL Server continuously using native CDC instead of SSIS batch jobs
  • 04 Consolidate branch or plant databases into a single operational SQL Server hub

Common sync patterns

Cross-engine sync

Keep the same dataset live in both Citus and SQL Server, so each workload runs on the engine that suits it.

Migration with zero-downtime cutover

When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.

Shared reference data between services

Services that own separate databases stay consistent on the records they share, without a custom replication layer.

What you can sync between Citus and SQL Server

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 SQL Server objects How this pairing syncs
Schemas Standard Postgres namespaces used to scope what a sync user can read and write. Schemas Namespaces (dbo and custom) used to organize synced tables. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. Custom fields on either side are included in the mapping.
Views Curated projections over distributed data, often used as read-only sync sources. Views Read-side projections used as outbound sync sources. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. Tables The primary sync target; rows map to records in connected systems. Local tables is specific to Citus and Tables to SQL Server — 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. Columns Field-level mapping targets with T-SQL types. Sequences is specific to Citus and Columns to SQL Server — 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. Primary and Unique Keys Match keys for idempotent upserts and conflict handling. Distributed tables is specific to Citus and Primary and Unique Keys to SQL Server — each maps to any object or custom field on the other side.
Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. CDC Change Tables System-populated tables holding captured inserts, updates, and deletes for consumers. Reference tables is specific to Citus and CDC Change Tables to SQL Server — each maps to any object or custom field on the other side.

How changes propagate between Citus and SQL Server

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 SQL Server 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 SQL Server as a row-level write, with types converted between the two schemas.

SQL Server Citus Sub-second propagation

DetectionChanges in SQL Server are captured at the source via change data capture — no polling loop against its API. SQL Server Native Change Data Capture (CDC).

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

Rate-limit considerations

  • SQL Server: No API rate limits; throughput depends on instance resources, licensing tier, and connection limits.
What ships with Citus ⇄ SQL Server

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Citus or SQL Server 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 SQL Server record.

Observability

Monitoring

Track your Citus ⇄ SQL Server 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 SQL Server.

How the Citus and SQL Server 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

SQL Server

Integration surface
SQL over the TDS wire protocol (Tabular Data Stream), via ODBC/JDBC/ADO.NET drivers
Authentication
Database credentials entered as a connection string or as parameters (host/user/password) in the Create New Sync page
Change detection
SQL Server Native Change Data Capture (CDC); a DBA runs a one-time setup script with sysadmin privileges to enable CDC and create Stacksync wrapper procedures
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance resources, licensing tier, and connection limits
SQL Server setup guide
How it works

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

    Choose tables

    Pick the Citus and SQL Server 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 ⇄ SQL Server
    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 SQL Server
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Citus and SQL Server 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 465 integrations available for Citus and SQL Server.

Popular · 6 of 465
All Citus integrations All SQL Server integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own