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Data warehouse ⇄ Database

BigQuery to Reltio integration — real-time, two-way sync

Keep BigQuery and Reltio 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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Why teams connect BigQuery and Reltio

Connect Reltio and BigQuery 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 Reltio's rows in BigQuery, 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 Reltio where the services that read from it get them at normal query latency.

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

Common use cases

  • 01 Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • 02 Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools
  • 03 Feed Interactions (transactions, visits, events) into Reltio to enrich entity profiles, then read them back for 360-degree reporting.
  • 04 Mirror the Reltio Activity Log and change history into a database for audit, lineage, and governance reporting.

Common sync patterns

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

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

Operational data in the warehouse, minus the pipeline

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

What you can sync between BigQuery and Reltio

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.

BigQuery objects Reltio objects How this pairing syncs
Partitioned tables Synced like regular tables; partition columns map to target fields. Matches (Potential Matches) Candidate duplicate pairs produced by match rules; read to review, and resolved with merge, unmerge, or not-a-match actions to control survivorship. Partitioned tables is specific to BigQuery and Matches (Potential Matches) to Reltio — each maps to any object or custom field on the other side.
Clustered tables Supported; clustering is transparent to the sync. Activity Log Immutable audit trail of changes to entities and relations via /activities; read-only, used for history, lineage, and compliance reporting. Clustered tables is specific to BigQuery and Activity Log to Reltio — each maps to any object or custom field on the other side.
Datasets Organizational container — you pick which dataset’s tables to sync. Data Change Requests (DCR) Stewardship change proposals routed through approval workflows; read and written to feed or track governed edits to golden records. Datasets is specific to BigQuery and Data Change Requests (DCR) to Reltio — each maps to any object or custom field on the other side.
Projects Connection scope: the service account grants access per project. Reference Data (RDM) Managed lookup and reference values (country codes, standardized values, hierarchies); read and updated so downstream systems share consistent reference data. Projects is specific to BigQuery and Reference Data (RDM) to Reltio — each maps to any object or custom field on the other side.
Tables The syncable unit: only tables can be synced per the Stacksync docs. Entities Golden records for each configured entity type (for example Organization, Individual/Contact, Location, or Product); full CRUD via /entities, so records are created, updated, and deleted, and Reltio matches and merges them by survivorship rules. Tables is specific to BigQuery and Entities to Reltio — each maps to any object or custom field on the other side.

How changes propagate between BigQuery and Reltio

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.

BigQuery Reltio Sub-second propagation

DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").

DeliveryEach detected change is written to Reltio through its API, with automatic retries and rate-limit backoff.

Reltio BigQuery Interval-based propagation

DetectionStacksync polls Reltio for changes on an incremental schedule, reading only records changed since the previous pass. Polling the REST API on updateTime (epoch-ms), for example filter=gt(updateTime,<timestamp>), for entities and relations changed past a stored.

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

Rate-limit considerations

  • BigQuery: Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes.
  • Reltio: Reltio applies per-tenant API throttling and returns HTTP 429 (Too Many Requests) when limits are exceeded; there is no single fixed request-per-second cap published for all tenants, and throttling is tuned per tenant and environment. Large loads and reads use bulk create/update and the asynchronous export/jobs API rather than row-by-row calls.
What ships with BigQuery ⇄ Reltio

Connect BigQuery and Reltio for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in BigQuery or Reltio instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery or Reltio 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 BigQuery or Reltio record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between BigQuery and Reltio.

How the BigQuery and Reltio connectors work

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide

Reltio

Integration surface
Reltio REST API (Data API) — /entities, /relations, /interactions, /activities, plus Match, RDM (reference data), and Data Change Request endpoints; base URL https://{environment}.reltio.com/reltio/api/{tenantId}
Authentication
OAuth 2.0 bearer tokens obtained from Reltio's central auth server (POST https://auth.reltio.com/oauth/token, client-credentials or password grant, application/x-www-form-urlencoded) and sent as Authorization: Bearer <token>; access tokens expire after about 60 minutes and are renewed with a refresh token, and are scoped per API (entities_api, relations_api, interactions_api, configuration_api, graphs_api)
Change detection
Polling the REST API on updateTime (epoch-ms), for example filter=gt(updateTime,<timestamp>), for entities and relations changed past a stored watermark. Reltio has no CDC log external tools consume; separately, Reltio's event streaming can publish entity change events (created, changed, removed) to a customer-configured message queue (Amazon SQS/SNS, Google Pub/Sub, Azure Service Bus, or Kafka), which is a queue feed rather than HTTP webhooks.
Capabilities
read · write
Rate limits
Reltio applies per-tenant API throttling and returns HTTP 429 (Too Many Requests) when limits are exceeded; there is no single fixed request-per-second cap published for all tenants, and throttling is tuned per tenant and environment. Large loads and reads use bulk create/update and the asynchronous export/jobs API rather than row-by-row calls.
How it works

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

    Choose tables

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

BigQuery and Reltio 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
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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 467 integrations available for BigQuery and Reltio.

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