Real-time
Two-way sync
Changes in Citus or Gmail instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Communications
Citus to Gmail integration — real-time, two-way sync
Keep Citus and Gmail 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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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Citus and Gmail
Turn the messages, calls, and events Gmail handles into live rows in Citus, and write back to trigger new outbound communication, with both sides in sync in seconds.
Engineers reach communications tools like Gmail through APIs, which means auth tokens, webhooks, delivery callbacks, and rate limits, all maintained forever and all shaped differently for every tool. The data those tools produce, who was contacted, what was sent, and what came back, would be simple to use if it lived in Citus next to everything else.
Stacksync mirrors Messages, Threads, Labels, Drafts from Gmail into Views, Sequences, Distributed tables, Reference tables in Citus and keeps both sides in sync in real time. Communication activity lands in the database as ordinary rows you can query and join, and rows your code writes, such as a queued outbound message or an updated contact, flow back into Gmail so the tool and the database never disagree.
There is no webhook endpoint to host, no rate limit to babysit, and no nightly export that leaves your services reading yesterday's activity.
Common use cases
- 01 Read Attachments and message metadata into a warehouse or document store for retention, discovery, and compliance reporting.
- 02 Mirror Labels with pipeline or ticket states so triage done in an external tool is reflected inside the inbox.
- 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
One contact list across both
Recipients and contacts stay consistent between Gmail and Citus, so a phone number or email corrected on either side is current the next time either system uses it.
React to activity as it happens
Sends, replies, answered calls, or completed meetings arrive in Citus as row changes, so triggers, jobs, and services can respond in near real time.
One integration pattern for every channel
Each communications tool looks like tables in the database, so adding email, voice, or messaging is configuration rather than a new codebase.
What you can sync between Citus and Gmail
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 | Gmail objects | How this pairing syncs | |
|---|---|---|---|
| Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | Drafts Unsent messages; created and updated from templates or sequence tools so reps review before sending from their own mailbox. | Reference tables is specific to Citus and Drafts to Gmail — each maps to any object or custom field on the other side. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Attachments File payloads referenced by message part; read out to storage or a document system for archival and compliance workflows. | Local tables is specific to Citus and Attachments to Gmail — 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. | History The incremental change log keyed by historyId; used for efficient delta sync so only mailbox changes since the last cursor are fetched. | Schemas is specific to Citus and History to Gmail — 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. | Messages Individual emails with headers, body, and label state; read out to a CRM or warehouse for activity logging, and sent or modified two-way from sales tools. | Views is specific to Citus and Messages to Gmail — 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. | Threads Conversation groupings that keep replies together; synced so a CRM timeline or support desk shows the full exchange, not isolated messages. | Sequences is specific to Citus and Threads to Gmail — 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. | Labels User and system labels (INBOX, SENT, custom); applied and removed via sync to mirror pipeline stages or triage states from an external system. | Distributed tables is specific to Citus and Labels to Gmail — each maps to any object or custom field on the other side. |
How changes propagate between Citus and Gmail
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 Gmail 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 Gmail through its API, with automatic retries and rate-limit backoff.
Gmail Citus Sub-second propagation
DetectionGmail notifies Stacksync of record changes through webhook events. Incremental sync via users.history.list from a stored historyId cursor, plus real-time push notifications through Google Cloud Pub/Sub watch on the.
DeliveryEach detected change is applied to Citus as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Gmail: Quota is measured in units per user per second (e.g. messages.list = 5 units, messages.send = 100 units) against a 250 quota-unit/user/second limit and a daily project cap; exceeding limits returns 429 with exponential backoff expected.
What ships with Citus ⇄ Gmail
Connect Citus and Gmail for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–Gmail connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Citus or Gmail 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 Gmail record.
Observability
Monitoring
Track your Citus ⇄ Gmail 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 Gmail.
How the Citus and Gmail 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
Gmail
- Integration surface
- Gmail API (REST, v1)
- Authentication
- OAuth 2.0 via Google — user-authorized consent with granular scopes (gmail.readonly, gmail.modify, gmail.send, gmail.labels); restricted scopes require Google's app verification for production use
- Change detection
- Incremental sync via users.history.list from a stored historyId cursor, plus real-time push notifications through Google Cloud Pub/Sub watch on the mailbox (watch must be renewed at least every 7 days)
- Capabilities
- read · write · webhooks
- Rate limits
- Quota is measured in units per user per second (e.g. messages.list = 5 units, messages.send = 100 units) against a 250 quota-unit/user/second limit and a daily project cap; exceeding limits returns 429 with exponential backoff expected.
How it works
How to connect Citus to Gmail — 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 Gmail 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
Gmail
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Citus and Gmail 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 ⇄ GmailCustomers 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 GmailCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Citus and Gmail integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Citus and Gmail: authenticate both systems, choose the objects to sync (such as Citus's Reference tables and Local tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Common patterns for Citus and Gmail: One contact list across both; React to activity as it happens; One integration pattern for every channel. Recipients and contacts stay consistent between Gmail and Citus, so a phone number or email corrected on either side is current the next time either system uses it.
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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). Gmail: Gmail API (REST, v1). Authentication: OAuth 2.0 via Google — user-authorized consent with granular scopes (gmail.readonly, gmail.modify, gmail.send, gmail.labels); restricted scopes require Google's app verification for production use. Stacksync manages authentication, retries, and rate limits on both sides.
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Gmail: A mailbox watch expires after 7 days and must be re-issued; missing the renewal silently stops real-time updates until the next poll. Citus: The managed cloud offering is Azure Cosmos DB for PostgreSQL, which is Citus under a Microsoft brand. Stacksync's field mapping accounts for these differences between Citus and Gmail without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Citus and Gmail records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Citus and Gmail connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Citus–Gmail integration in-house.
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
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