Hi @Abhinay_Raj,
Thanks for reaching out Microsoft Fabric Community Support.
REST API calls are an excellent choice when flexibility, cross-platform integration, and security are priorities. They are particularly useful for small to medium-sized datasets and custom data retrieval needs.
However, the approach has limitations for high-volume or real-time data transfer due to potential API rate limits and performance bottlenecks. if the use case involves large-scale data or frequent updates, direct database connectivity or batch processing might be more efficient alternatives.
Direct database connectivity offers a more straightforward approach if performance and real-time updates are priorities. Use the Oracle Database connector in Synapse Pipelines or Azure Data Factory to establish a connection.
After the connection is set up, configure a pipeline to query and transfer data into Fabric Lakehouse. Use Delta tables as the destination format for optimized analytics. This approach avoids the overhead of setting up APIs and offers direct data access but requires secure network connectivity between Oracle Cloud and Fabric, such as through a VPN or private link.
File-based integration is a simpler alternative for batch data transfers: Export table data from Oracle Cloud to a CSV or Parquet file. Store these files in Oracle Object Storage or a shared location accessible to Fabric. upload these files in Fabric Lakehouse using pipelines or manual uploads.
Use Fabric's transformation capabilities to convert the files into Delta tables. While this method is the easiest to set up, it is less efficient for large datasets and doesn’t support real-time updates. However, it’s suitable for periodic or one-time data transfers where simplicity is a priority.
Best practices
- securing data during transfer, especially for REST API and direct connections, by using encryption protocols like HTTPS and setting up firewalls.
- For APIs, implement pagination and filtering to manage data size and avoid rate limits.
- Direct connections should use optimized queries and partitioning for better performance.
- With file-based approaches, ensure file integrity and schema consistency.
Limitations:
- REST API calls are versatile and enable fine-grained control over data but can be limited by API quotas and performance for large datasets.
- Direct connectivity is faster and better for real-time use but requires robust network security.
- File-based methods are simple and low-maintenance but are best suited for batch processing.
Choose the method based on the frequency, volume, and complexity of your data needs. Let me know if you need any additiponal help here?
Thanks,
Prashanth Are
MS Fabric community support.
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