when should we use data fusion over etl data flows
Best Answer
-
Fusion is fantastic for relatively simple joins on large datasets that number in the tens of millions of rows and greater.
The ETL and MySQL dataflows are different ways to accomplish the same end goal, allowing the user to pick the method they are most comfortable with. Some users work best in SQL, so the MySQL ETL recreates that, whereas some people prefer visual drag and drop dataflows which is Magic ETL.
All things being equal, I believe that Magic ETL is slightly more performant than MySQL ETL however.
The choice further comes down to how complicated some of your dataflows are/can be, and how they will be managed. It's easier to see what's happening from a high level with Magic, but can data transformations tricky to perform. MySQL allows for basically any data transformation to occur, but you need to go into each transform to view the logic.
0
Answers
-
Fusion is fantastic for relatively simple joins on large datasets that number in the tens of millions of rows and greater.
The ETL and MySQL dataflows are different ways to accomplish the same end goal, allowing the user to pick the method they are most comfortable with. Some users work best in SQL, so the MySQL ETL recreates that, whereas some people prefer visual drag and drop dataflows which is Magic ETL.
All things being equal, I believe that Magic ETL is slightly more performant than MySQL ETL however.
The choice further comes down to how complicated some of your dataflows are/can be, and how they will be managed. It's easier to see what's happening from a high level with Magic, but can data transformations tricky to perform. MySQL allows for basically any data transformation to occur, but you need to go into each transform to view the logic.
0
Categories
- All Categories
- Product Ideas
- 2.1K Ideas Exchange
- Connect
- 1.3K Connectors
- 309 Workbench
- 7 Cloud Amplifier
- 10 Federated
- Transform
- 663 Datasets
- 119 SQL DataFlows
- 2.3K Magic ETL
- 823 Beast Mode
- Visualize
- 2.6K Charting
- 86 App Studio
- 46 Variables
- Automate
- 193 Apps
- 483 APIs & Domo Developer
- 86 Workflows
- 23 Code Engine
- AI and Machine Learning
- 23 AI Chat
- 4 AI Projects and Models
- 18 Jupyter Workspaces
- Distribute
- 117 Domo Everywhere
- 283 Scheduled Reports
- 11 Software Integrations
- Manage
- 143 Governance & Security
- 11 Domo Community Gallery
- 49 Product Releases
- 13 Domo University
- Community Forums
- 41 Getting Started
- 31 Community Member Introductions
- 116 Community Announcements
- 5K Archive