Real-time
Two-way sync
Changes in Citus or Microsoft Teams instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Business productivity
Citus to Microsoft Teams integration — real-time, two-way sync
Keep Citus and Microsoft Teams 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
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Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Citus and Microsoft Teams
Mirror Microsoft Teams's data into Citus so your own code can read and write it like any other table, with changes flowing both ways in seconds.
Engineers integrate with tools like Microsoft Teams through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Citus.
Stacksync mirrors Channel Messages, Chats & Chat Messages, Team Members & Users, Online Meetings from Microsoft Teams into Local tables, Schemas, Views, Sequences in Citus and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into Microsoft Teams, so the tool and the database never disagree.
Common use cases
- 01 Notify an ops channel when a sync detects failed or conflicting records that need review.
- 02 Sync team membership from HR or identity systems so channels match the org chart.
- 03 Write CRM or billing records into reference tables so distributed queries can join operational context locally on every node.
- 04 Use a Citus cluster as the scalable operational store behind a customer-facing app while syncing summaries back to internal tools.
Common sync patterns
Automate Microsoft Teams from your codebase
Write to the synced tables in Citus and Stacksync propagates the change into Microsoft Teams, replacing custom integration code.
React to changes as they happen
Updates in Microsoft Teams arrive as row changes in Citus, so triggers, jobs, and services can respond in near real time.
One integration pattern for the whole stack
Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.
What you can sync between Citus and Microsoft Teams
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 | Microsoft Teams objects | How this pairing syncs | |
|---|---|---|---|
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Teams Team containers provisioned or read to mirror org and project structure. | Distributed tables is specific to Citus and Teams to Microsoft Teams — 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. | Channels Channel targets used for routing synced notifications and updates. | Reference tables is specific to Citus and Channels to Microsoft Teams — each maps to any object or custom field on the other side. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Channel Messages Posted messages read for archiving or written to broadcast record changes. | Local tables is specific to Citus and Channel Messages to Microsoft Teams — 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. | Chats & Chat Messages 1:1 and group chat content read under protected-API access for compliance use. | Schemas is specific to Citus and Chats & Chat Messages to Microsoft Teams — each maps to any object or custom field on the other side. | |
| Views Curated projections over distributed data, often used as read-only sync sources. | Team Members & Users Membership synced with identity, HR, or CRM ownership data. | Views is specific to Citus and Team Members & Users to Microsoft Teams — 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. | Online Meetings Meeting records synced with scheduling and CRM activity timelines. | Sequences is specific to Citus and Online Meetings to Microsoft Teams — each maps to any object or custom field on the other side. |
How changes propagate between Citus and Microsoft Teams
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 Microsoft Teams 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 written to Microsoft Teams through its API, with automatic retries and rate-limit backoff.
Microsoft Teams Citus Sub-second propagation
DetectionMicrosoft Teams notifies Stacksync of record changes through webhook events. Graph change notifications (webhooks) for messages and membership.
DeliveryEach detected change is applied to Citus as a row-level write, with types converted between the two schemas.
What ships with Citus ⇄ Microsoft Teams
Connect Citus and Microsoft Teams for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–Microsoft Teams connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Citus or Microsoft Teams 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 Microsoft Teams record.
Observability
Monitoring
Track your Citus ⇄ Microsoft Teams 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 Microsoft Teams.
How the Citus and Microsoft Teams 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
Microsoft Teams
- Integration surface
- REST API (Microsoft Graph)
- Authentication
- OAuth 2.0 via Microsoft Entra ID; reading message content at scale requires Microsoft-approved protected-API access
- Change detection
- Graph change notifications (webhooks) for messages and membership; delta queries on some resources
- Capabilities
- read · write · webhooks
How it works
How to connect Citus to Microsoft Teams — 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 Citus and Microsoft Teams with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Citus
connected
Microsoft Teams
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Citus and Microsoft Teams 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 · Citus ⇄ Microsoft TeamsCustomers 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.
Citus Microsoft TeamsCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Citus and Microsoft Teams integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Citus and Microsoft Teams: authenticate both systems, choose the objects to sync (such as Citus's Distributed tables and Reference tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
On the Microsoft Teams side: Channel Messages, Chats & Chat Messages, Team Members & Users, Online Meetings, plus custom fields where Microsoft Teams exposes them. On the Citus side: Local tables, Schemas, Views, Sequences. 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.
-
Common patterns for Citus and Microsoft Teams: Automate Microsoft Teams from your codebase; React to changes as they happen; One integration pattern for the whole stack. Write to the synced tables in Citus and Stacksync propagates the change into Microsoft Teams, replacing custom integration code.
-
Citus: PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node. Authentication: Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options). Microsoft Teams: REST API (Microsoft Graph). Authentication: OAuth 2.0 via Microsoft Entra ID; reading message content at scale requires Microsoft-approved protected-API access. Stacksync manages authentication, retries, and rate limits on both sides.
-
Microsoft Teams: Teams has no standalone API; all programmatic access goes through Microsoft Graph alongside the rest of Microsoft 365. Citus: Because shard data lives on worker nodes, log-based CDC is more involved than on single-node Postgres and depends on the Citus version and hosting (including the Azure managed service). Stacksync's field mapping accounts for these differences between Citus and Microsoft Teams 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
Every pair below is a real-time, two-way sync. Search all 371 integrations available for Citus and Microsoft Teams.
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