HANA, BLU, Hekaton, and Oracle 12c vs. Teradata and Greenplum – November 2013

Catch Me If You Can (musical)
(Photo credit: Wikipedia)

I would like to point out a very important section in the paper on Hekaton on the Microsoft Research site here. I will quote the section in total:


An analysis done early on in the project drove home the fact that a 10-100X throughput improvement cannot be achieved by optimizing existing SQL Server mechanisms. Throughput can be increased in three ways: improving scalability, improving CPI (cycles per instruction), and reducing the number of instructions executed per request. The analysis showed that, even under highly optimistic assumptions, improving scalability and CPI can produce only a 3-4X improvement. The detailed analysis is included as an appendix. 

The only real hope is to reduce the number of instructions executed but the reduction needs to be dramatic. To go 10X faster, the engine must execute 90% fewer instructions and yet still get the work done. To go 100X faster, it must execute 99% fewer instructions. This level of improvement is not feasible by optimizing existing storage and execution mechanisms. Reaching the 10-100X goal requires a much more efficient way to store and process data. 

This is important because it confirms the difference in a Level 3 and a Level 2 columnar implementation as described here. It is just not possible for a Level 2 implementation with a row-based join engine to achieve the performance of a Level 3 implementation. This will allow the Level 3 implementations: HANA, BLU, Hekaton, and Oracle 12c to distance themselves from the Level 2 products: Teradata and Greenplum; by more than 10X… and this is a very significant advantage.

Related articles

Database Computing is Supercomputing… Some external reading: May 2013

Superman: Doomsday & Beyond
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I would like to recommend to you John Appleby’s post  here on the HANA blog site. While the title suggests the article is about HANA, in fact it is about trends in computing and processors… and very relevant to posts here past, present, and upcoming…

I would also recommend Curt Monash’s site. His notes on Teradata here mirror my observation that a 30%-50% performance boost per release cycle is the target for most commercial databases… and what wins in the general market. This is why the in-memory capabilities offered by HANA and maybe DB2 BLU are so disruptive. These products should offer way more than that… not 1.5X but 100X in some instances.

Finally I recommend “What Every Programmer Should Know About Memory” by Ulrich Drepper here. This paper provides a great foundation for the deep hardware topics to come.

Database computing is becoming a special case, a commercial case, of supercomputing… high-performance computing (HPC) to those less inclined to superlatives. Over the next few years the differentiation between products will increasingly be due to the use of high-performance computing techniques: in-memory techniques, vector processing, massive parallelism, and use of HPC instruction sets.

This may help you to get ready…