Real-time
Two-way sync
Changes in Namely or Snowflake instantly reflect in both systems. No stale data, no manual imports.
Human resources ⇄ Data warehouse
Namely to Snowflake integration — real-time, two-way sync
Keep Namely and Snowflake 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
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Why teams connect Namely and Snowflake
Land the people and organization records from Namely in Snowflake 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 Snowflake next to everything else the company measures.
Stacksync syncs Profiles, Job Titles, Job Tiers, Groups from Namely into tables in Snowflake continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Snowflake, 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 Land CRM and ERP records in Snowflake continuously so BI reflects business systems without nightly batch ETL
- 02 Activate modeled Snowflake tables by syncing scores and attributes back into CRM fields sales can act on
- 03 Map Job Titles and Job Tiers into a warehouse dimension table so leveling and seniority stay consistent across HR, finance, and BI reporting.
- 04 Push Groups and Teams (departments, locations, team categories) into downstream apps to keep org structure and reporting lines aligned.
Common sync patterns
Queryable history for planning and audit
A continuously synced copy in Snowflake gives you a durable, queryable record of how Namely's records change over time, for headcount planning and audit questions.
Write-back of computed values
Segments, rollups, or risk flags computed in Snowflake 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 Snowflake as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.
What you can sync between Namely and Snowflake
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.
| Namely objects | Snowflake objects | How this pairing syncs | |
|---|---|---|---|
| Job Tiers Leveling hierarchy grouping zero-to-many Job Titles; read to map seniority into warehouse dimension tables. | Tasks Scheduled SQL used to transform synced data after it lands. | Job Tiers is specific to Namely and Tasks to Snowflake — each maps to any object or custom field on the other side. | |
| Groups Departments and locations that organize Profiles; synced to keep org structure aligned with a warehouse or IdP. | VARIANT Columns Semi-structured JSON payloads stored alongside relational columns. | Groups is specific to Namely and VARIANT Columns to Snowflake — each maps to any object or custom field on the other side. | |
| Teams Teams and team categories a Profile belongs to; read and written for org-chart and provisioning workflows. | Virtual Warehouses The compute a sync's queries run on, sized independently of storage. | Teams is specific to Namely and Virtual Warehouses to Snowflake — each maps to any object or custom field on the other side. | |
| Reports Saved Namely reports returned as JSON snapshots that update instantly; read-only feeds for headcount and roster analytics. | Databases Top-level containers that scope which data a sync can touch. | Reports is specific to Namely and Databases to Snowflake — each maps to any object or custom field on the other side. | |
| Profile Fields Metadata describing standard and company-defined custom field sections; read to discover schema and generate mappings. | Schemas Namespaces within a database used to organize synced tables. | Profile Fields is specific to Namely and Schemas to Snowflake — each maps to any object or custom field on the other side. | |
| Events Home-feed items such as announcements, birthdays, anniversaries, and new arrivals; typically read-only into comms tools. | Tables The main landing and activation target for synced records. | Events is specific to Namely and Tables to Snowflake — each maps to any object or custom field on the other side. |
How changes propagate between Namely and Snowflake
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.
Namely Snowflake 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 Snowflake as a row-level write, with types converted between the two schemas.
Snowflake Namely Sub-second propagation
DetectionChanges in Snowflake are captured at the source via change data capture — no polling loop against its API. The setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism.
DeliveryEach detected change is written to Namely through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- 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.
- Snowflake: No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time.
What ships with Namely ⇄ Snowflake
Connect Namely and Snowflake for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Namely–Snowflake connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Namely or Snowflake 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 Namely or Snowflake record.
Observability
Monitoring
Track your Namely ⇄ Snowflake sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Namely and Snowflake.
How the Namely and Snowflake connectors work
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.
Snowflake
- Integration surface
- SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
- Authentication
- Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles
- Change detection
- Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism
- Capabilities
- read · write · CDC
- Rate limits
- No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time
How it works
How to connect Namely to Snowflake — 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 Namely and Snowflake with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Namely
connected
Snowflake
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Namely and Snowflake 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 · Namely ⇄ SnowflakeCustomers 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.
Namely SnowflakeCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Namely and Snowflake integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Namely and Snowflake: authenticate both systems, choose the objects to sync (such as Namely's Job Tiers and Groups), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Yes — Stacksync ships production-grade connectors for both Namely and Snowflake. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on Namely: No webhooks; integrations poll GET endpoints and compare the updated_at / created_at timestamps on Profiles and related objects to detect changes. On Snowflake: Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the Snowflake side: Databases, Schemas, Tables, Views, plus custom fields where Snowflake exposes them. On the Namely side: Profiles, Job Titles, Job Tiers, Groups. Stacksync auto-detects both schemas and converts types between the two systems.
-
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 Namely and Snowflake: Queryable history for planning and audit; Write-back of computed values; HR data in the warehouse, minus the pipeline. A continuously synced copy in Snowflake gives you a durable, queryable record of how Namely's records change over time, for headcount planning and audit questions.
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:
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