The presentation given by Andrew Pavlo “MapReduce and Parallel DBMSs”, embedded below for reference, identifies the following 3 sweet spots for MapReduce:
- “Read Once” data sets
- Allows for quick-and-dirty data analysis
- Semi-Structured Data
- Can easily store semi-structured data which would otherwise be awkward to be stored in RDBMS
- Limited Budget Operations
- the alternative, parallel DBMSs are expensive
What can MapReduce learn from Databases?
- Fast query times.
- Supporting tools.
What can Databases learn from MapReduce?
- Ease of use, “out of box” experience.
- Attractive fault tolerance properties.
- Fast load times.