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QMigrator for Microsoft Fabric
Quadrant Technologies
QMigrator for Microsoft Fabric
Quadrant Technologies
QMigrator for Microsoft Fabric
Quadrant Technologies
Real time data integration, replication from any source Database to Microsoft Fabric
Data Source Integration to Microsoft Fabric using QMigrator
QMigrator enables organizations to move data across different sources to target platforms (on-prem/cloud). With its scalable Kubernetes framework, QMigrator redefines Data Replication by handling the data replication autonomously with minimal human intervention and monitoring. More details at qmigrator.ai.
Comprehensive Database Replication to Microsoft Fabric
QMigrator supports replication from all major relational and NoSQL databases, including:
- Oracle
- SQL Server
- PostgreSQL
- MySQL
- DB2
- MongoDB
- Teradata
- Snowflake
- SAP HANA
- ...and more
Target destinations on Microsoft Fabric include:
- Fabric Lakehouse
- Fabric Data Warehouse
- Fabric SQL Database
- Open Mirroring
Key Capabilities
- Autonomous Job Agent: Dynamically assesses source, target, and cluster capacity to schedule optimized replication jobs.
- Zero-Touch Operation: Automated monitoring and retry mechanisms for job stability and reliability.
- High Performance: Supports parallelized replication of billions of rows across hundreds of tables.
- Change Data Capture (CDC): Enables continuous sync with minimal lag for real-time data availability.
Example Replication Metrics
Metric | Value |
---|---|
Source | Oracle (8 core / 32 GB) |
Target | Microsoft Fabric (F8 SKU) |
Row Count | 3.8 Billion |
Table Count | 232 |
Data Size | 1,024 GB |
Initial Load Time | 4 hr 9 mins (~4.11 GB/min) |
CDC Throughput | 556 MB/min |
CDC Volume | 116,524 transactions/min (1 hr 26 mins) |
Note: Replication times and throughput may vary based on source database type, network capacity, and target Fabric configurations.
Deployment & Support
- Custom Deployment & Proof-of-Concept (POC) Services
- Comprehensive Documentation & Training Programs
- Built for enterprise-grade reliability at scale
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