SyncSage Documentation | Syncsage Docs

SyncSage's Data Warehouse module provides a centralized, scalable, and secure environment to store, manage, and analyze your data. By integrating with Snowflake, users can seamlessly ingest structured and semi-structured data from 680+ connectors (via Fivetran) and leverage powerful tools for querying, transformation, and visualization.

Key Features

•Snowflake Integration: Direct connectivity for data ingestion and management
•Schema Management: Organize tables and schemas for efficient data access
•SQL Query Editor: Execute and save SQL queries with real-time results
•Storage Optimization: Monitor usage, enable compression, and reduce costs
•Performance Metrics: Track query execution times and data throughput

Access the Data Tables sidebar to manage schemas and tables within Snowflake.

3.1 Key Functionalities

Browse Tables

Filter tables by name using the Search bar
View metadata (rows, size) for each table

Example: Production Schema

Table Name	Rows	Size
customers	1.2M	256MB
orders	5.8M	1.2GB

Additional Features

Refresh Schemas: Click Refresh to update the list after structural changes
Schema Permissions: Assign roles (e.g., ANALYST, ADMIN) to restrict access

The SQL Query Editor allows users to interact directly with Snowflake data.

4.1 Writing and Executing Queries

Write Queries

Use the editor to write SQL (e.g., joins, aggregations).

SELECT 
  customers.id,
  customers.name,
  COUNT(orders.id) AS total_orders,
  SUM(orders.amount) AS total_spent
FROM customers
LEFT JOIN orders ON customers.id = orders.customer_id
GROUP BY customers.id, customers.name
HAVING COUNT(orders.id) > 5
ORDER BY total_spent DESC
LIMIT 10;

Additional Features

Run Queries: Click Run Query to execute
Save Queries: Save frequently used scripts to Saved Queries

Monitor and optimize storage usage via the Storage Management sidebar.

5.1 Key Metrics

Metric	Value	Description
Total Storage Used	2.5 TB / 5 TB	Current vs. allocated storage
Active Tables	156	Tables across 8 schemas
Growth Rate	+85 GB/month	Average monthly storage increase

5.2 Optimization Strategies

Auto-Compression

Reduces storage footprint (e.g., saved 400 GB)

Archival Candidates

Identify stale data for archival (e.g., 150 GB)

Cost Projection

Current Monthly Cost: $2,500
Projected (3 Months): $3,200
Potential Savings: $450

Access the Warehouse Performance sidebar to monitor and enhance query efficiency.

6.1 Critical Metrics

Average Query Execution Time: 250ms
Data Throughput: 1.2 GB/s
Concurrent Users: 50 (peak)

6.2 Best Practices

1. Indexing

Create indexes on frequently queried columns

2. Warehouse Scaling

Adjust Snowflake warehouse size during peak loads

3. Query Caching

Leverage Snowflake's result caching for repeated queries

4. Incremental Syncs

Set for large datasets (e.g., sync only new Salesforce leads)

Example Configuration:

{
  "sync_mode": "incremental",
  "cursor_field": "last_modified_date",
  "cursor_granularity": "seconds"
}

5. Auto-Suspend

Use in Snowflake to save costs during idle periods

Snowflake Command:

ALTER WAREHOUSE FIVETRAN_WH 
SET AUTO_SUSPEND = 300; -- Suspend after 5 minutes of inactivity

Data Warehouse Integration

Key Features

2.1 Connecting Snowflake to SyncSage

1. Provide Snowflake Credentials

2. Test Connection

3. Sync Data

2.2 Post-Ingestion Actions

3.1 Key Functionalities

Browse Tables

Example: Production Schema

Additional Features

4.1 Writing and Executing Queries

Write Queries

Additional Features

5.1 Key Metrics

5.2 Optimization Strategies

Auto-Compression

Archival Candidates

Cost Projection

6.1 Critical Metrics

6.2 Best Practices

1. Indexing

2. Warehouse Scaling

3. Query Caching

4. Incremental Syncs

5. Auto-Suspend

Q: How do I troubleshoot slow queries?

Q: Can I share schemas with team members?

Q: What happens if I exceed storage limits?

For Further Assistance