Big data architecture with Redis
August 23, 2019
Big data architecture with Redis
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with Redis
The R&D department uses Redis as 'in-memory' hot data storage (data storage layer of a machine learning big data architecture).
Pros
- Low latency
- Support hundreds of connections
Cons
- Significant learning curve
- Could be costly if not designed right
- Scalable solution.
- Cost effective after some optimizations.
- Price
- Product Features
- Prior Experience with the Product
- Existing Relationship with the Vendor
High availability and low latency were crucial features that turned the table for Redis adoption.
Redshift has relatively high latency and thus produces unscalable solution.
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