It has been clear for a long time that relational databases are ill-suited for analytical processing. The problem is fundamental: relational databases are designed to retrieve all elements from a few records, while analytical queries typically read all records but only a few elements. Until recently, database developers were able to overcome the problem with clever design and powerful hardware. Today, the largest databases - hundreds or thousands of terabytes - are too big for this to work at an acceptable price. Thus, the quest for alternatives is on.

But let’s back up a bit. Relational databases are inefficient at analyzing all sizes of databases, not just the largest. Companies may have met their critical needs by throwing money at the problem, but they have also rejected less important applications that couldn’t justify the cost. This suggests there is a significant hidden demand for analytical applications of all sizes if costs can be reduced.

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