Data Recovery in HANA, TimesTen, and SQLFire

There is a persistent myth, like a persistent cough, that claims that in-memory databases lose data when a hardware failure takes down a node because memory is volatile and non-persistent. This myth is marketing, not architecture. Most RDBMS products: including Oracle, TimesTen, and HANA; have three layers where data exists: in-memory (think SGA for Oracle), in…

SQLFire, Exalytics, TimesTen, and HANA… a quick comparison

As you may have noticed I’m looking at in-memory databases (IMDB) these days… Here are some quick architectural observations on VMWare‘s SQLFire, Oracle’s Exalytics and TimesTen offerings, and SAP HANA. It is worth noting up front that I am looking to see how these products might be used to build a generalized data mart or…

Numbers Everyone Should Know

Some of you have seen me build simple models to do a reality-check on architecture (see here, for example). Here are some metrics from a great presentation by Jeff Dean, a Google fellow. Numbers Everyone Should Know L1 cache reference 0.5 ns Branch mispredict 5 ns L2 cache reference 7 ns Mutex lock/unlock 25 ns…

Cloud Computing and Data Warehousing: Part 4 – IMDB Data Warehouse in a Cloud

In the previous blogs on this topic (Part 1, Part 2, Part 3) I suggested that: Shared-nothing is required for an EDW, An EDW is not usually under-utilized, There are difficulties in re-distributing sharded, shared-nothing data to provide elasticity, and A SAN cannot provide the same IO bandwidth per server as JBOD… nor hit the…

More on Exalytics Capacity…

I found myself wondering where did the rule-of-thumb for Exalytics  that suggests that TimesTen can use 800GB of a 1TB memory space… and requires 400GB of that space for work tables leaving room for 400GB of user data… come from (it is quoted everywhere… here is an example… see question #13). Sure enough, this rule…