5-minute tutorial
Copy Data from Microsoft SQL Server to Synapse with ingestr
Learn how to move Microsoft SQL Server data into Synapse with a repeatable CLI workflow using ingestr.
What you'll learn
Prerequisites
- Python 3.8 or higher installed
- SQL Server instance running
- SQL Server Authentication or Windows Authentication configured
- TCP/IP protocol enabled in SQL Server Configuration Manager
- Firewall rules for port 1433
- Azure Synapse workspace
- Azure Active Directory credentials
Step 1: Install ingestr
Install ingestr in seconds using pip. Choose the method that works best for you:
Recommended: Using uv (fastest)
# Install uv first if you haven't already
pip install uv
# Run ingestr using uvx
uvx ingestrAlternative: Global installation
# Install globally using uv
uv pip install --system ingestr
# Or using standard pip
pip install ingestrVerify installation: Run ingestr --version to confirm it's installed correctly.
Step 2: Your First Migration
Let's copy a table from Microsoft SQL Server to Synapse. This example shows a complete, working command you can adapt to your needs.
Set up your connections
Microsoft SQL Server connection format:
mssql://username:password@host:port/databaseParameters:
- • username: SQL Server login
- • password: Login password
- • host: Server name or IP
- • port: Port number (default 1433)
- • database: Database name
- • encrypt: Use encryption (true/false)
- • trustServerCertificate: Trust certificate
Synapse connection format:
synapse://username:password@workspace.sql.azuresynapse.net/databaseParameters:
Run your first copy
Copy the entire users table from Microsoft SQL Server to Synapse:
ingestr ingest \
--source-uri 'mssql://sa:MyPass123@localhost:1433/AdventureWorks' \
--source-table 'dbo.Customers' \
--dest-uri 'synapse://username:password@workspace.sql.azuresynapse.net/database' \
--dest-table 'raw.Customers'What this does:
- • Connects to your Microsoft SQL Server database
- • Reads all data from the specified table
- • Creates the table in Synapse if needed
- • Copies all rows to the destination
Command breakdown:
--source-uriYour source database--source-tableTable to copy from--dest-uriYour destination--dest-tableWhere to write data
Step 3: Verify your data
After the migration completes, verify your data was copied correctly:
Check row count in Synapse:
-- Run this in Synapse
SELECT COUNT(*) as row_count
FROM raw.Customers;
-- Check a sample of the data
SELECT *
FROM raw.Customers
LIMIT 10;Advanced Patterns
Once you've mastered the basics, use these patterns for production workloads.
Only copy new or updated records since the last sync. Perfect for daily updates.
ingestr ingest \
--source-uri 'mssql://sa:MyPass123@localhost:1433/AdventureWorks' \
--source-table 'public.orders' \
--dest-uri 'synapse://username:password@workspace.sql.azuresynapse.net/database' \
--dest-table 'raw.orders' \
--incremental-strategy merge \
--incremental-key updated_at \
--primary-key order_idHow it works: The merge strategy updates existing rows and inserts new ones based on the primary key. Only rows where updated_at has changed will be processed.
Common Use Cases
Ready-to-use commands for typical Microsoft SQL Server to Synapse scenarios.
Daily Customer Data Sync
Keep your analytics warehouse updated with the latest customer information every night.
# Add this to your cron job or scheduler
ingestr ingest \
--source-uri 'mssql://sa:MyPass123@localhost:1433/AdventureWorks' \
--source-table 'public.customers' \
--dest-uri 'synapse://username:password@workspace.sql.azuresynapse.net/database' \
--dest-table 'analytics.customers' \
--incremental-strategy merge \
--incremental-key updated_at \
--primary-key customer_idHistorical Data Migration
One-time migration of all historical records to your data warehouse.
# One-time full table copy
ingestr ingest \
--source-uri 'mssql://sa:MyPass123@localhost:1433/AdventureWorks' \
--source-table 'public.transactions' \
--dest-uri 'synapse://username:password@workspace.sql.azuresynapse.net/database' \
--dest-table 'warehouse.transactions_historical'Development Environment Sync
Copy production data to your development Synapse instance (with sensitive data excluded).
# Copy sample data to development
ingestr ingest \
--source-uri 'mssql://sa:MyPass123@localhost:1433/AdventureWorks' \
--source-table 'public.products' \
--dest-uri 'synapse://username:password@workspace.sql.azuresynapse.net/database' \
--dest-table 'dev.products' \
--limit 1000 # Only copy 1000 rows for testingChoosing a Microsoft SQL Server to Synapse data integration tool
If you're comparing ways to move Microsoft SQL Server data into Synapse, start with the path you can run locally, review in code, and schedule later.
What is the best data integration tool to move data from Microsoft SQL Server to Synapse?
ingestr is a good fit when you want an open-source CLI for Microsoft SQL Server to Synapse ingestion. You can run it from your terminal, CI, or a scheduled job, then move the same pipeline into Bruin Cloud when you need orchestration, lineage, and monitoring.
Can this run as an incremental pipeline?
Yes. Use snapshot-plus-incremental or time-based extraction when the source supports it. That keeps the first load simple while making later runs smaller and easier to monitor.
When should I use Bruin Cloud with ingestr?
Use Bruin Cloud when the Microsoft SQL Server to Synapse pipeline needs schedules, alerts, data quality checks, audit trails, or catalog and lineage visibility for the rest of the team.
Troubleshooting Guide
Solutions to common issues when migrating from Microsoft SQL Server to Synapse.
Connection refused or timeout errors
Check your connection details:
- Enable TCP/IP in SQL Server Configuration Manager
- Check SQL Server Browser service is running
- Verify Windows Firewall allows SQL Server
- Ensure Mixed Mode authentication if using SQL login
Authentication failures
Common authentication issues:
- Enable TCP/IP in SQL Server Configuration Manager
- Check SQL Server Browser service is running
- Verify Windows Firewall allows SQL Server
- Ensure Mixed Mode authentication if using SQL login
Schema or data type mismatches
Handling data type differences:
- ingestr automatically handles most type conversions
- Microsoft SQL Server: NVARCHAR for Unicode support
- Microsoft SQL Server: Hierarchyid for tree structures
- Microsoft SQL Server: Spatial data types for geographic data
- Microsoft SQL Server: XML and JSON support
Performance issues with large tables
Optimize large data transfers:
- Use incremental loading to process data in chunks
- Run migrations during off-peak hours
- Split very large tables by date ranges using interval parameters
Ready to scale your data pipeline?
You've learned how to migrate data from Microsoft SQL Server to Synapse with ingestr. For production workloads with monitoring, scheduling, and data quality checks, explore Bruin Cloud.