Real-time
Real-time sync
Changes in Lusha or Snowflake instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Data warehouse
Lusha to Snowflake integration — real-time data sync
Keep Lusha 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.
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Lusha and Snowflake
Get the data locked inside Lusha into Snowflake as live tables, and send results back where Lusha can use them, without writing a pipeline.
Lusha is a read-only source: Stacksync reads its data in real time and delivers it into Snowflake, so Snowflake always reflects the current state of Lusha — without exports, scripts, or schedulers.
Whatever Lusha is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.
Common use cases
- 01 Enrich new CRM leads with work emails and direct dials the moment they are created.
- 02 Backfill missing phone numbers on an existing contact list stored in a database or warehouse.
- 03 Land CRM and ERP records in Snowflake continuously so BI reflects business systems without nightly batch ETL
- 04 Activate modeled Snowflake tables by syncing scores and attributes back into CRM fields sales can act on
Common sync patterns
History that outlives the tool
A continuously synced copy in Snowflake preserves a queryable record even as data ages out of Lusha or gets changed inside it.
Analytics on Lusha's data
Records and events from Lusha land in Snowflake as queryable tables, current within seconds and ready to join with the rest of the warehouse.
Cross-tool reporting
Combine Lusha's data with data from every other synced system to answer questions no single tool can.
What you can sync between Lusha 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.
| Lusha objects | Snowflake objects | How this pairing syncs | |
|---|---|---|---|
| Phone Numbers Direct-dial and mobile numbers appended for outbound calling workflows. | Stages File staging areas used for bulk loads into synced tables. | Phone Numbers is specific to Lusha and Stages to Snowflake — each maps to any object or custom field on the other side. | |
| Prospecting Results Search-based lists of people and companies matching filters, used to seed lead lists. | Tasks Scheduled SQL used to transform synced data after it lands. | Prospecting Results is specific to Lusha and Tasks to Snowflake — each maps to any object or custom field on the other side. | |
| Bulk Enrichment Requests Batch lookups that enrich multiple records per request, used to backfill large contact lists rather than one-off calls. | VARIANT Columns Semi-structured JSON payloads stored alongside relational columns. | Bulk Enrichment Requests is specific to Lusha and VARIANT Columns to Snowflake — each maps to any object or custom field on the other side. | |
| Person Profiles Contact-level enrichment results (work emails, phone numbers, title, company) returned per lookup. | Virtual Warehouses The compute a sync's queries run on, sized independently of storage. | Person Profiles is specific to Lusha and Virtual Warehouses to Snowflake — each maps to any object or custom field on the other side. | |
| Company Profiles Firmographic records (industry, size, location) appended to account or company rows. | Databases Top-level containers that scope which data a sync can touch. | Company Profiles is specific to Lusha and Databases to Snowflake — each maps to any object or custom field on the other side. | |
| Email Addresses Work emails written into CRM contact fields during enrichment. | Schemas Namespaces within a database used to organize synced tables. | Email Addresses is specific to Lusha and Schemas to Snowflake — each maps to any object or custom field on the other side. |
How changes propagate between Lusha 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.
Lusha Snowflake Interval-based propagation
DetectionStacksync polls Lusha for changes on an incremental schedule, reading only records changed since the previous pass. Data is fetched on demand per lookup, so syncs poll or trigger enrichment when source records change.
DeliveryEach detected change is applied to Snowflake as a row-level write, with types converted between the two schemas.
Snowflake Lusha 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.
DeliveryLusha does not accept inbound record writes, so this direction carries requests rather than records: Lusha's output flows back as field updates on the originating Snowflake records.
Rate-limit considerations
- Lusha: Lookups consume credits and are subject to the platform's API rate limits.
- Snowflake: No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time.
What ships with Lusha ⇄ Snowflake
Connect Lusha and Snowflake for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Lusha–Snowflake connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Lusha 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 Lusha or Snowflake record.
Observability
Monitoring
Track your Lusha ⇄ Snowflake sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Lusha and Snowflake.
How the Lusha and Snowflake connectors work
Lusha
- Integration surface
- REST API
- Authentication
- API key
- Change detection
- Not event-driven; data is fetched on demand per lookup, so syncs poll or trigger enrichment when source records change
- Capabilities
- read
- Rate limits
- Lookups consume credits and are subject to the platform's API rate limits.
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 Lusha 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 Lusha 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.
Lusha
connected
Snowflake
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Lusha 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 · Lusha ⇄ 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.
Lusha SnowflakeCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Lusha and Snowflake integration FAQ
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Yes. Stacksync provides a managed, real-time integration between Lusha and Snowflake — Lusha is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
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Change detection on Lusha: Not event-driven; data is fetched on demand per lookup, so syncs poll or trigger enrichment when source records change. 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.
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On the Lusha side: Company Profiles, Email Addresses, Phone Numbers, Prospecting Results, plus custom fields where Lusha exposes them. On the Snowflake side: Streams, Stages, Tasks, VARIANT Columns. Stacksync auto-detects both schemas and converts types between the two systems.
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Lusha is a read-only source, so this integration runs one-way: Stacksync reads from Lusha in real time and delivers into Snowflake. Field mapping and monitoring work the same as for two-way pairs.
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Common patterns for Lusha and Snowflake: History that outlives the tool; Analytics on Lusha's data; Cross-tool reporting. A continuously synced copy in Snowflake preserves a queryable record even as data ages out of Lusha or gets changed inside it.
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Lusha: REST API. Authentication: API key. Snowflake: 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. Stacksync manages authentication, retries, and rate limits on both sides.
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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