There is a compound effect in building memory optimized features and being a distributed database that can put a lot more cores at work and cache a lot more dat

There is a compound effect in building memory optimized features and being a distributed database that can put a lot more cores at work and cache a lot more data in a cluster: - In-memory row stores. Super fast for updates and point lookups - Memory optimized hash joins that minimized cash misses. Great for analytical/reporting use cases - Vectorization for columnstore query processing. Super fast aggregations that work best when data is cached in memory