Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Production-ready
- Good performance
- Active development
Cons
- Pricing varies
- Setup required
Pros
- Unified platform combining data, analytics, and ML
- Built on Apache Spark for efficient large-scale processing
- Strong collaboration features with real-time notebooks
- Auto-scaling reduces infrastructure management
Cons
- High costs at scale—major concern across reviews