Reltio + Snowflake
Connect Reltio and Snowflake to Put Trusted Master Data Where It's Actually Used
Push clean, unified master data from Reltio directly into Snowflake for analytics, reporting, and AI-ready data pipelines.
Why integrate Reltio and Snowflake?
Reltio is a cloud-native master data management (MDM) platform that resolves, enriches, and governs entity data across customers, products, locations, and more. Snowflake is the cloud data platform where analytics teams run queries, build data models, and power business intelligence. The two fit together well: Reltio keeps your data trusted and deduplicated, while Snowflake makes it fast, scalable, and accessible to every downstream consumer.
Automate & integrate Reltio & Snowflake
Use case
Sync Golden Customer Records to Snowflake for 360° Analytics
When Reltio resolves and merges customer profiles into a single golden record, tray.ai can automatically push those unified profiles into Snowflake. Analysts can then join master customer data with transaction history, support tickets, and behavioral events to build comprehensive customer 360 views — without having to work around unresolved, duplicate records.
Use case
Propagate Product Master Data Updates to Snowflake in Real Time
Product attributes, hierarchies, and classifications managed in Reltio can be automatically streamed to Snowflake whenever records are created or updated. Product catalog data used in sales reporting, inventory analytics, and ecommerce dashboards stays consistent and current without waiting for overnight batch jobs.
Use case
Load Resolved HCP and HCO Data into Snowflake for Life Sciences Analytics
Life sciences companies managing Healthcare Provider (HCP) and Healthcare Organization (HCO) master data in Reltio can use tray.ai to continuously load resolved and validated records into Snowflake. This powers compliant field force analytics, territory planning, and CRM performance dashboards backed by trusted entity data.
Use case
Trigger Snowflake Data Pipeline Refreshes When Reltio Records Change
When a master data event occurs in Reltio — a merge, split, or enrichment update — tray.ai can trigger downstream Snowflake pipeline refreshes, dbt model runs, or stored procedure executions. Analytical layers update when master data actually changes, not on a rigid schedule that may or may not line up.
Use case
Audit Reltio Data Quality Metrics in Snowflake for Governance Reporting
Reltio captures data quality scores, match confidence levels, and survivorship metadata for every master record. By flowing this metadata into Snowflake alongside the golden records themselves, data governance teams can build dashboards that track MDM health, monitor duplicate rates, and measure the impact of data stewardship over time.
Use case
Enrich Snowflake Entity Tables with Reltio Cross-Reference IDs
Reltio maintains cross-reference identifiers that link master entities back to source systems like Salesforce, SAP, Oracle, and legacy CRMs. Syncing these cross-reference mappings into Snowflake lets data engineers reliably join disparate source datasets through a unified identity backbone, without building brittle custom key-mapping tables.
Use case
Automate Periodic Full Snapshots of Reltio Entities to Snowflake
For historical analysis and compliance archiving, tray.ai can schedule periodic full extracts of Reltio entity populations — all active customer or supplier records, for example — and load complete snapshots into Snowflake. These time-stamped snapshots support slowly changing dimension tracking, regulatory lookbacks, and trend analysis across MDM data over time.
Get started with Reltio & Snowflake integration today
Reltio & Snowflake Challenges
What challenges are there when working with Reltio & Snowflake and how will using Tray.ai help?
Challenge
Handling Reltio's Nested JSON Entity Model in Snowflake
Reltio stores master data as richly nested JSON objects with attributes, cross-references, relations, and metadata all embedded in a flexible schema. Snowflake's columnar storage model requires these complex payloads to be flattened or transformed before loading — and managing that transformation consistently at scale is genuinely hard for most ETL approaches.
How Tray.ai Can Help:
tray.ai provides a visual data transformation layer where teams can map Reltio's nested entity structure to flat Snowflake columns using drag-and-drop field mapping, JSONPath expressions, and reusable transformation logic. No custom parsing code, and when the schema changes it doesn't take an engineering sprint to catch up.
Challenge
Maintaining Referential Integrity Across Merged and Split Entities
Reltio continuously resolves duplicates by merging records, and it can also split previously merged records when new information arrives. These operations change the canonical entity URI, which means downstream Snowflake tables that use Reltio entity IDs as foreign keys can become stale or broken if merge and split events aren't properly handled.
How Tray.ai Can Help:
tray.ai workflows can listen specifically for merge and split event types from Reltio and execute targeted Snowflake UPDATE and DELETE operations to repair affected foreign key references, so cross-reference tables and fact table joins stay consistent after every identity resolution event.
Challenge
Scaling High-Volume Entity Sync Without Hitting API Rate Limits
Enterprises often manage millions of customer or product records in Reltio, and syncing large populations through the REST API row-by-row can quickly exhaust API rate limits or stretch into multi-hour sync windows — which defeats the point of having near-real-time data in Snowflake.
How Tray.ai Can Help:
tray.ai supports bulk extraction using Reltio's Search API with pagination, parallel processing of result batches, and Snowflake's staged bulk-load mechanism (COPY INTO) to maximize throughput. Built-in retry logic and rate-limit awareness mean large syncs complete reliably without anyone watching over them.
Challenge
Keeping Snowflake Schema Aligned with Reltio Tenant Configuration Changes
Reltio's MDM configuration is tenant-specific, and organizations regularly add new entity types, attribute groups, or relationship types as their MDM program matures. Each change can introduce new fields that need to show up in Snowflake table schemas, and tracking these manually leads to pipeline failures and quietly missing data.
How Tray.ai Can Help:
tray.ai workflows can be updated through a visual interface when Reltio configurations evolve. Conditional branching logic handles optional or newly introduced fields gracefully — inserting NULL values for missing attributes rather than failing — while alerting data engineers when schema drift is detected.
Challenge
Securing Sensitive Master Data in Transit Between Reltio and Snowflake
Master data in Reltio often includes personally identifiable information (PII), protected health information (PHI), and other regulated attributes. Keeping this data encrypted in transit, properly access-controlled, and compliant with GDPR, HIPAA, and CCPA requirements adds real complexity to integration design.
How Tray.ai Can Help:
tray.ai includes encrypted credential storage, TLS-encrypted data transport, and role-based access controls that restrict which users and workflows can access sensitive Reltio data. Compliance-focused masking and field-filtering logic can be embedded directly in workflows to prevent regulated attributes from being written to unauthorized Snowflake environments.
Start using our pre-built Reltio & Snowflake templates today
Start from scratch or use one of our pre-built Reltio & Snowflake templates to quickly solve your most common use cases.
Reltio & Snowflake Templates
Find pre-built Reltio & Snowflake solutions for common use cases
Template
Reltio Golden Record Created → Insert into Snowflake
Whenever a new golden record is created or finalized in Reltio, tray.ai maps the entity attributes and inserts a new row into the corresponding Snowflake table, keeping the data warehouse current with the latest resolved master data.
Steps:
- Listen for a new entity creation or merge event via Reltio webhook or polling trigger
- Transform and map Reltio entity attributes to the target Snowflake table schema
- Execute an INSERT or MERGE statement in Snowflake to add or update the golden record
Connectors Used: Reltio, Snowflake
Template
Reltio Record Updated → Upsert into Snowflake Table
When an existing Reltio master record is enriched, corrected, or re-merged, this template detects the change and performs an upsert into the corresponding Snowflake table, so downstream analytics always reflect the latest authoritative version of each entity.
Steps:
- Detect entity update events in Reltio using webhook notifications or change data polling
- Retrieve the full updated record payload from the Reltio REST API
- Run a MERGE statement in Snowflake to update the existing row or insert if new
Connectors Used: Reltio, Snowflake
Template
Scheduled Reltio Entity Bulk Export → Snowflake Batch Load
On a configurable schedule, this template extracts a full or incremental population of Reltio entities using the Reltio Search API, transforms the results, and bulk-loads them into Snowflake using staged file loading for high-throughput data warehouse updates.
Steps:
- Execute a scheduled Reltio entity search query to retrieve all records modified since last run
- Transform and serialize entity payloads into a structured format compatible with Snowflake
- Stage the data file and execute a COPY INTO command to bulk-load records into Snowflake
Connectors Used: Reltio, Snowflake
Template
Reltio Match & Merge Event → Snowflake Cross-Reference Table Update
When Reltio performs a match-and-merge operation, consolidating duplicate entities into a single golden record, this template updates the cross-reference and identity resolution tables in Snowflake so downstream joins and identity graphs stay accurate.
Steps:
- Capture match-and-merge completion events from Reltio via webhook
- Extract the surviving golden record URI and the list of absorbed source record cross-references
- Update Snowflake cross-reference dimension tables to reflect the new merged entity identity
Connectors Used: Reltio, Snowflake
Template
Snowflake Query Result → Create or Update Reltio Entity Attributes
This reverse-direction template lets enriched or scored data computed in Snowflake — customer lifetime value, risk scores, segmentation labels — be written back into Reltio as additional attributes on the corresponding master record, closing the loop between analytics and MDM.
Steps:
- Execute a scheduled Snowflake query to retrieve entities with newly computed attribute values
- Match each Snowflake row back to the corresponding Reltio entity using a persistent ID or cross-reference
- Call the Reltio REST API to patch the enriched attribute values onto the golden record
Connectors Used: Snowflake, Reltio
Template
Reltio Data Quality Score Change → Snowflake Governance Dashboard Update
When Reltio recalculates data quality scores or completeness metrics for a set of entities, this template pushes the updated scores into a Snowflake governance table, keeping data quality dashboards and stewardship reports current without manual intervention.
Steps:
- Poll Reltio for entities whose data quality or completeness scores have changed since last sync
- Extract entity IDs, quality dimensions, scores, and evaluation timestamps from Reltio
- Insert or update records in a Snowflake data quality metrics table for downstream dashboard consumption
Connectors Used: Reltio, Snowflake