Review of "“One Size Fits All”: An Idea Whose Time Has Come and Gone"

Problem: In this paper, the author argues that the traditional DBMS has tried "one size fits all" but failed in face of data warehouse system and streaming systems and this attempt will continue to fail dramatically in the future as more and more diverse need of data storage comes out.

Key idea: In the data warehouse example the author cites that most enterprises have two storage systems, one stores the OLTP data, another just scraps data from this OLTP system and allow doing business intelligence queries on it. But the two storage system requires different optimization techniques, like bitmap index, materialized view. Common practice in vendor products include using a common front-end to cover two underlying bottoms, one for OLTP and one for data warehousing, but this structure makes marketing these product confusing. In the stream processing example, the author argues that traditional OLTP systems is incapable of handling this "firehose" of data generated by sensor networks. And the speed of the traditional OLTP systems is also not satisfying for real-time events queries. Through the analysis of different domains like sensor networks, scientific databases and text search, the author concludes that there will be many different domain specific databases come out in the future, and database systems are entering an interesting period.

Will this paper be influential in 10 years? I think so, it identifies the key reason why people are developing all kinds of different storage systems. And justifies new systems like Google F1 which aims to provide both OLTP and OLAP interfaces for upper level applications. This trend also generates more and more research opportunities in specialized storage systems and the processing frameworks on top of them.