Insights
Azure ADF vs Google Data fusion: Based on our experience working with our client projects there were challenges in brings in data from ADF to GCS.
As a long term solution we have recommended our clients to go with GCP DF instead of Azure ADF especially when clients are looking for GCP cloud native solutions and applications
Features
Azure Data Factory VS Google cloud Data Fusion - Capablitiy Comparison Over View
| # | Capabitiy Feature | Sub Feature | ADF | Data Fusion | Additional Comments |
|---|---|---|---|---|---|
| 1 | Integration | Batch Real Time | 1 ** | 1 1 |
Both Fully supported ADF - Events hub & Kafka |
| 2 | Orchestration | - | 1 | 0 | - |
| 3 | Transformation | Joins/Unicros/Reanames | ** | 1 | - |
| 4 | Auto Scaling | - | 1 | ** | Data fusion - Need to write script for automation |
| 5 | Data Volume | large Volume | 0 | 1 | ADF - low to medium volumes Data fusion - Large to very large volumes ( > 20 milion, > 20 columns ) |
| 6 | Pipeline Backup | - | 1 | 1 | Data fusion - Need to write scripts for automation |
| 7 | Data Linage | End to end | 0 | 1 | - |
| 8 | Source Connectors | - | 1 | 1 | ADF - 70+ |
| 9 | Targets connectors ( sinks ) | - | 0 | 1 | - |
| 10 | Compute | - | 1 | 1 | - |
| 11 | Data Processing | - | 1 | 1 | - |
| 12 | Support CDAP | - | 0 | 1 | - |
- Contact us for detailed report
- Legend 1 - Full support, 0 - No support **partial support
- Cloud view based on our past solutions recommendations
Our solution insights – Vertex AI vs Databricks vs Open-source tools:
Features
Vertex AI Data Bricks VS Open Source tools - Capability Comparison Over View
| # | Capabitiy Feature | Data Bricks | Vertex AI | Open Source Tools [prophet, delta share, interpret ml ] |
Additional Comments |
|---|---|---|---|---|---|
| 1 | Core AI capabilites | ** | 1 | ** | There are gray lines between needs and wants that's not addressed here |
| 2 | Cloud Native Implementaion | ** | 1 | 0 | - |
| 3 | Portablity / Open | ** | ** | 1 | Needs significant effort compared OSS tools |
| 4 | Regional Availability | 0 | 1 | ** | - |
| 5 | AI and Optimization framework | ** | 1 | ** | - |
| 6 | User / persons productivity | ** | 1 | ** | Great in vertex AI due to tight integration with BQ, BQ Auto ML, Data Studio |
| 7 | Time to market & price | 0 | 1 | ** | with non avaliblity of the market palce for databricks bill end of 2022 It's not recommended to consider |
| 8 | Product as a service Data as a product | 1 | 1 | 0 | - |