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well, I would like to say the OLAP Cube is just re-rising now. There are 1000+ companies deployed Apache Kylin (OLAP Engine for Big Data) in the past 5 years, f

well, I would like to say the OLAP Cube is just re-rising now. There are 1000+ companies deployed Apache Kylin (OLAP Engine for Big Data) in the past 5 years, for 100+B rows, for 100+ concurrent users...many different use cases are based that technology...it works very well with BI tools and so friendly to analysts who are using such "old fashion" every day over the decade (how hard for them to be Data Scientists?) check more here: http://kylin.apache.org/community/poweredby.html http://kylin.apache.org/community/poweredby.html

Merick 7y ago
+1 for Apache Kylin, it's a great project and awesome open source community. If anyone is curious about what modern OLAP is capable of, check it out. If you want an alternative take on where OLAP is today and what it is capable of, I usually recommend this article: https://kyligence.io/blog/olap-analytics-is-dead-really/ https://kyligence.io/blog/olap-analytics-is-dead-really/
- shadowsun7 7y ago
  There are huge problems with that piece. For starters, OLAP != OLAP cube. Columnar databases and OLAP cubes are both designed for OLAP workloads. They are simply different architectures. Therefore, it is impossible to argue that 'OLAP is dead' — it cannot be dead, because OLAP is simply a type of database usage. At this point you might say, "oh, OLAP cubes refer to an abstraction, it can be implemented using columnar stores!" — and I would point you to 40 years worth of academic research that stretches back to the early 80s. The OLAP cube or data cube refers to a specific type of data structure. It just so happens that vendors like to use the term 'OLAP cube' even when they are using a columnar engine under the hood, because it sells well.