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Data warehouse ⇄ Human resources

Google Cloud Platform to Namely integration — real-time, two-way sync

Keep Google Cloud Platform and Namely 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 Google Cloud Platform and Namely

Land the people and organization records from Namely in Google Cloud Platform as live tables for workforce reporting, without extract jobs, and write computed results back where Namely can use them.

Workforce data is some of the most requested data in the warehouse and some of the most awkward to move: the record types are many, the fields carry sensitive personal information, the APIs are strict, and hand-built extract jobs go stale or break quietly. Whether Namely is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in Google Cloud Platform next to everything else the company measures.

Stacksync syncs Job Titles, Job Tiers, Groups, Teams from Namely into tables in Google Cloud Platform continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Google Cloud Platform, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Namely where the HR team acts on them. You configure which records and fields cross over, and in which direction, instead of maintaining pipeline code.

Common use cases

  • 01 Publish change events to Pub/Sub so downstream services react to record updates as they happen.
  • 02 Push Groups and Teams (departments, locations, team categories) into downstream apps to keep org structure and reporting lines aligned.
  • 03 Feed Namely Reports as JSON into a database on a schedule for roster, turnover, and diversity dashboards without manual CSV exports.

Common sync patterns

Write-back of computed values

Segments, rollups, or risk flags computed in Google Cloud Platform sync back onto the matching records in Namely, where the HR team sees them in the system they already use.

HR data in the warehouse, minus the pipeline

People and organization records from Namely arrive in Google Cloud Platform as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.

Headcount and cost joined with everything else

Analysts combine Namely's workforce records with finance, product, or operational data already in Google Cloud Platform for reporting the HR system cannot produce on its own.

What you can sync between Google Cloud Platform and Namely

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.

Google Cloud Platform objects Namely objects How this pairing syncs
Pub/Sub topics Event streams used to move change events between systems in near real time. Profiles The core employee record (personal, job, contact, and compensation fields); synced two-way via GET/POST/PUT with updated_at driving incremental polling. Pub/Sub topics is specific to Google Cloud Platform and Profiles to Namely — each maps to any object or custom field on the other side.
Firestore documents Document data read and written through the Firestore API for app-facing syncs. Job Titles Job title definitions; read and written so titles stay aligned with an HRIS, directory, or reporting dimension. Firestore documents is specific to Google Cloud Platform and Job Titles to Namely — each maps to any object or custom field on the other side.
Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. Job Tiers Leveling hierarchy grouping zero-to-many Job Titles; read to map seniority into warehouse dimension tables. Spanner tables is specific to Google Cloud Platform and Job Tiers to Namely — each maps to any object or custom field on the other side.
BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. Groups Departments and locations that organize Profiles; synced to keep org structure aligned with a warehouse or IdP. BigQuery datasets is specific to Google Cloud Platform and Groups to Namely — each maps to any object or custom field on the other side.
BigQuery tables The primary analytics destination, written through load jobs or the Storage Write API and queried with SQL. Teams Teams and team categories a Profile belongs to; read and written for org-chart and provisioning workflows. BigQuery tables is specific to Google Cloud Platform and Teams to Namely — each maps to any object or custom field on the other side.
Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. Reports Saved Namely reports returned as JSON snapshots that update instantly; read-only feeds for headcount and roster analytics. Cloud SQL databases is specific to Google Cloud Platform and Reports to Namely — each maps to any object or custom field on the other side.

How changes propagate between Google Cloud Platform and Namely

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.

Google Cloud Platform Namely Sub-second propagation

DetectionGoogle Cloud Platform pushes changes as they happen — webhook events backed by change data capture. Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery.

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

Namely Google Cloud Platform Interval-based propagation

DetectionStacksync polls Namely for changes on an incremental schedule, reading only records changed since the previous pass. No webhooks.

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

Rate-limit considerations

  • Google Cloud Platform: Quotas are set per service and per project; BigQuery, Pub/Sub, and Cloud SQL each enforce their own limits.
  • Namely: Namely's public docs do not publish a fixed request quota; the REST API returns standard HTTP status codes, so integrations should throttle and back off on 429/5xx responses.
What ships with Google Cloud Platform ⇄ Namely

Connect Google Cloud Platform and Namely for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Google Cloud Platform–Namely connection.

Real-time

Two-way sync

Changes in Google Cloud Platform or Namely instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Google Cloud Platform or Namely 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 Google Cloud Platform or Namely record.

Observability

Monitoring

Track your Google Cloud Platform ⇄ Namely sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Google Cloud Platform and Namely.

How the Google Cloud Platform and Namely connectors work

Google Cloud Platform

Integration surface
Per-service REST and gRPC APIs; BigQuery speaks SQL and Cloud SQL exposes standard database wire protocols
Authentication
IAM service accounts with OAuth 2.0 tokens
Change detection
Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery tables
Capabilities
read · write · CDC · webhooks
Rate limits
Quotas are set per service and per project; BigQuery, Pub/Sub, and Cloud SQL each enforce their own limits

Namely

Integration surface
REST API (JSON over HTTPS)
Authentication
OAuth 2.0 authorization-code grant, or a personal access token sent as a Bearer token; all calls run over HTTPS against https://{subdomain}.namely.com/api/v1
Change detection
No webhooks; integrations poll GET endpoints and compare the updated_at / created_at timestamps on Profiles and related objects to detect changes
Capabilities
read · write
Rate limits
Namely's public docs do not publish a fixed request quota; the REST API returns standard HTTP status codes, so integrations should throttle and back off on 429/5xx responses.
How it works

How to connect Google Cloud Platform to Namely — 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 Google Cloud Platform and Namely 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
    Google Cloud Platform connected
    Namely connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Google Cloud Platform and Namely 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 · Google Cloud Platform ⇄ Namely
    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
    Google Cloud Platform Namely
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Google Cloud Platform and Namely 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.

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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 436 integrations available for Google Cloud Platform and Namely.

Popular · 4 of 436
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