Saturday, March 01, 2008

H-Store - a new architectural era, or just a toy?

Philip Howard's commentary Merchant relational databases: over-engineered and out-of-date? supports the idea that perhaps general purpose relational databases should now be treated as "legacy". He references a paper The End of an Architectural Era (It's time for a rewrite) by Michael Stonebraker and others from MIT.

My first thought was that RDBMS developers such as Oracle have seen off previous architectural challengers - most notably object oriented databases (OODBMS) - in the past 25-30 years. What makes Stonebraker's H-Store any different?

First, a quick summary of the paper:

  • RDBMSs were designed 30 years ago - since then memory and cpu have become faster, cheaper and bigger, changing the balance against magnetic (disc) storage
  • increasingly they are failing to meet today's complex challenges
  • niche solutions have overtaken "general purpose" RDBMS in many areas (eg data appliances for business intelligence; specialist text search engines; etc)
  • and now even OLTP, the "core competence" of the RDBMS, is no longer safe; a new approach (such as H-Store) can easily beat traditional RDBMS by cutting out non-functional architectural features (eg: redo logs stored on disc) and achieving the same goals (ACID transactions) in another way.

The paper claims that H-Store can beat a traditional RDBMS at TPC-C style benchmarks; an early version runs up to 80 times faster than "a very popular RDBMS" which itself underwent several days of tuning by a "professional DBA".

H-Store's secret sauce is that it is (in effect) single threaded. It makes the assumptions that all transactions are very fast; then it executes each transaction in turn. This gets rid of the need for complex read-consistency models. Other optimisations include keeping undo in memory (because transactions are short and sharp) and discarding it at the end of the transaction.

Well, go off and read the paper for the details, but here's what I think.

On the negative side:

  • As a comparative benchmark, this fails through insufficient disclosure. For a paper that passes as academic, there is remarkably little detail on what they actually did.
  • Stonebraker assumes that "most" OLTP systems can be represented by a hierarchical model - what he calls a "constrained tree application" (CTA). As a result these applications are relatively easy to partition over a shared-nothing architecture. I wonder whether this is really the case. Parts of your application may be like that, or they may be like that for some periods (during the online day, for example). But even OLTP applications need to manage longer transactions, complex reporting, and updates to the "read only" tables. In his example, he assumes (section 5.0) that the Items table is read only, so it doesn't break his tree and it can easily be replicated. But we know that new items will be added; others will be re-priced, re-categorised, phased out. Can that be handled without interrupting a 24/7 H-Store style application?
  • He also seems to assume that there is only one axis of partitioning - in his case, the warehouse. But over time, the main focus of interest changes. An order is taken at a shop; it is ordered from a warehouse; it is delivered to the customer. Different "CTAs" at each stage. How does the H-Store morph its representation through the course of the information lifecycle?

On the positive side, though, this represents a call to action for the traditional vendors.

  • Any performance specialist knows that the best way to tune something is to stop doing it. If we really can change the rules of the game, we can avoid all that expensive "insurance". We're used to making calculated design tradeoffs for performance; this could be just another one of those.
  • I suspect that the RDBMS vendors will (more or less rapidly) steal any really good ideas. Stonebraker states that "no [RDBMS] system has had a complete redesign since its
    . But, like the proverbial axe, RDBMS internals have been refreshed, a piece at a time. Oracle's database kernel has had at least two major rehashes in its lifetime. It's well within Oracle's or IBM's capability to incorporate the more realistic ideas from this paper, and to find a way to blend them with current state of the art.
  • They can also learn from the approach MySQL has taken of supporting multiple storage engines - horses for courses. Oracle already merges XML, relational and OLAP data stores; building in a high performance OLTP kernel to address specific classes of OLTP application is not at all inconceivable. Although it will lead to all sorts of information lifecycle difficulties, we are already used to migrating data from OLTP to OLAP; with good tool support it should be possible to work round the constraints that allow H-Store to dispense with so much that we normally take for granted.

I may revisit this paper to tease out other issues - for example Stonebraker rants against SQL (perhaps he's never got over Ingres being forced by the market to provide SQL rather than the more academically respectable Quel). H-Store uses C++, and may move to Ruby; the implication is that applications will be object-oriented, making row-by-row navigations (like so many J2EE apps, and suspiciously like COBOL/Codasyl) rather than being set-oriented.

Let's watch this space.

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