Recently there has been a lot of noise around in memory databases and how Exadata, Exalytics and SAP HANA compare to each other. Here are my two cents on the debate.
Why you can’t compare Exalytics to SAP Hana
It is the vision of SAP Hana to be used for both OLTP and analytics. As the name already suggests Exalytics just caters for analytics. Exalytics needs to be loaded from the data warehouse or transactional systems. Not needed for Hana. Everything already sits in memory. While Exalytics is near near realtime. Hana is realtime. However, currently there are not too many OLTP applications running on Hana. The problem is that applications need to be adapted or rewritten to make full use of HANA’s new architecture.This seems about to change. SAP has recently released a service pack for HANA that will allow it to do just that. However, the claim of being able to run OLTP and Analytics in the same in memory database remains somewhat unproven.
Why you can’t compare Exadata to SAP Hana
Exadata V3 now ships with 4 TB of RAM. Contrary to the claims of Oracle this does not make it an in-memory database. It lacks two important features:
- Most of the data still sits on disk. Mostly SSD. Still disk
- It lacks the optimized algorithms and design features (in memory indexes etc.) that have specifically been designed for in memory access.
How does HANA compare to Exadata/Exalytics then?
Well, it doesn’t. Oracle (or anyone else for that matter) still has to come up with a product that can be compared to HANA.
Use cases of SAP HANA
The number 1 use case for SAP HANA is for realtime operational business intelligence. True realtime BI now seems a distinct possibility. In this use case HANA represents the Interactive Sector as defined by Inmon et al. in their DW 2.0 book.
The other use case is similar to what Exalytics is used for. A performance booster for the data warehouse. In this scenario we load or replicate data into the in-memory database either directly from our OLTP systems or the data warehouse. This is what we have predominantly seen HANA being used for so far. However, this falls well short of the vision and long term strategy, namely to change the way we do databases.
The third use case of course and the end game for HANA is to run OLTP, data warehouse, and analytics all on HANA. Not very realistic at the moment. DRAM is still too costly.
What happens next?
This is the billion dollar question. Curt Monash thinks:
“Putting all that together, the analytic case for SAP HANA seems decently substantiated, there are years of experience with the technology and its antecedents, and column stores (including in-memory) are well-established for analytics via multiple vendors. The OLTP case for HANA, however, remains largely unproven. It will be interesting to see how it plays out.”
It will indeed be interesting to see how this plays out. SAP are currently heavily promoting HANA. There is a developer license available. You can rent an instance on AWS. SAP are pushing it hard for start-ups. I am sure that it will replace Oracle in many SAP implementations as the underlying database. It remains to be seen, however, if it can eat into the wider database market (the ultimate SAP objective). The other interesting question is: when will Oracle come up with a product that can compete head on with HANA? I believe there is plenty of time. The game hasn’t really started yet.
In the meantime Microsoft have also announced an in memory database named Hekaton for release in 2014/15. It seems to be for OLTP only and from what I read a bit of a joke. Interesting times indeed though.
The wider picture and Google
At the moment we are seeing some tectonic shifts in the technology space that we haven’t seen in a generation. New technologies like Hadoop, Impala, IMDBs, NoSQL, Cloud etc are emerging that can handle ever bigger data at an ever faster speed. These innovations will have knock on effects on the way we architect information systems and on enterprise architecture in general. I even believe that they will ultimately change the way we do business. Unknown to many, a lot of these innovations are pioneered by Google. Papers on MapReduce and the Google File System kicked off Hadoop. Google BigTable inspired a lot of the NoSQL databases we have seen recently. You may have heard of Impala from Cloudera. Again a brainchild of Google. Based on Google Spanner and probably more so their in-house RDBMS F1.
I would expect more innovation to come from that corner. After all Google is at the epicentre of the Big Data problem. They already have their own offering named BigQuery, which recently left the Beta phase. Doesn’t look like much right now but I expect them to up their game.
Of course you can ignore those trends but you do so at your own peril.
If you want to find out more about IMDBs and SAP Hana I recommend to read In-Memory Data Management: Technology and Applications by Hasso Plattner, one of the co-founders of SAP.