• Aster Data showed me a lot of customer names and deal sizes, across a bunch of industries (mainly enterprise rather than web). Yes, Aster’s market success is for real. (But almost all those details are NDA.)
• Sybase’s product plans for IQ are pretty impressive. (But the most interesting parts are, you guessed it, NDA.)
• I’ve kissed and made up* with ParAccel, now that they’ve replaced their CEO, replaced their marketing chief, and stopped the worst of the marketing nonsense I used to complain about. ParAccel has some interesting plans for ParAccel 3.0 which are, naturally, NDA.
• The Peoplesoft guys are doing it over again at Workday. Only this time, their platform isn’t a relational DBMS. Rather, it’s an in-memory, completely object-oriented data model, with disk used only on a “Just in case the power ever goes out” basis. (Thankfully, nothing at all about our conversation was NDA.)
• I’m finally feeling good about Northscale’s memcached-compatible persistent store Membase. The main reason is that they showed me a near-term path to interfaces that are richer than key-value. Also, Todd Hoff reassured me that even pure persistent memcached has a place.
• Rumor says that even the one app for which Facebook was using Cassandra — in-box search — has been decommissioned. On the other hand, numerous other scale-0ut DBMS (SQL or otherwise) seem to have Facebook footholds. But details are — all together now! — NDA.

*If you know ParAccel’s new marketing chief Michael Weir, you surely guessed I mean that only in a figurative sense.

From elsewhere:

• Daniel Abadi offered his analysis of Kickfire’s demise. In general I agree, but Daniel neglected to mention one hugely important factor — the chicken-egg negative effect of Kickfire’s lack of market or marketing traction. Customers were extremely reluctant to buy from Kickfire because they perceived, correctly, that Kickfire’s survivability was far from assured.
• While the InfiniDB forums suggest that there are at least a couple of production users of Calpont’s free InfiniDB, Calpont seemingly has a long way to go to be even as successful as Kickfire. But Calpont does have a bit of money to spend on lead generation; maybe some day they’ll even have actual customers.
• In a response to a question I messaged over, XtremeData tells me they have actual customers now. Press releases to follow.
• The admiration for the job Mark Hurd did at HP is in my opinion overstated. Sure, the financial/operational management appeared to work, but HP did little on Hurd’s watch to strengthen its reputation or customers’ loyalty. In particular:
  • HP’s analytics efforts have accomplished little.
  • HP’s data warehouse appliance efforts have failed pathetically.
  • From what I hear, HP’s execution in its Exadata partnership was not good.
  • HP’s server business in general is distinguished mainly by HP being a big company.
  • HP’s EDS acquisition has been rocky, not that EDS was sailing so smoothly on its own beforehand.
  • HP’s success in PCs amounts to “arguably, HP sucks a little less than the other guys”.
  • HP’s elite reputation is long gone (admittedly, for the most part that predates Hurd).
• Doug Henschen evidently favors really strong intellectual property protection for software, even forbidding plug-compatible reverse engineering. I agree with Doug up to the point that it should be forbidden to copy proprietary software, but I don’t see why he (or a court) would view such behavior as copying.

Most of what I get paid for is in some form or other consulting. (The same would be true for many other analysts.) And so I can be a bit stingy with my advice toward non-clients. But my non-clients are a distinguished and powerful group, including in their number Oracle, IBM, Microsoft, and most of the BI vendors. So here’s a bit of advice for them too.

Oracle. On the plus side, you guys have been making progress against your reputation for untruthfulness. Oh, I’ve dinged you for some past slip-ups, but on the whole they’ve been no worse than other vendors.’ But recently you pulled a doozy. The analyst reports section of your website fails to distinguish between unsponsored and sponsored work.* That is a horrible ethical stumble. Fix it fast. Then put processes in place to ensure nothing that dishonest happens again for a good long time.

*Merv Adrian’s “report” listed high on that page is actually a sponsored white paper. That Merv himself screwed up by not labeling it clearly as such in no way exonerates Oracle. Besides, I’m sure Merv won’t soon repeat the error — but for Oracle, this represents a whole pattern of behavior.

Oracle. And while I’m at it, outright dishonesty isn’t your only unnecessary credibility problem. You’re also playing too many games in analyst relations.

HP. Neoview will never succeed. Admit it to yourselves. Go buy something that can. 

Smaller BI vendors. Analytic DBMS evaluations commonly include BI strategy and tool selection as well. If an analytic DBMS expert tells you he needs to learn more about your product line, don’t blow him off. In fact, you should be particularly embracing anybody who’s shown a fondness for small DBMS vendors; maybe he or his clients will like small BI vendors as well. That means (among others) you, Jaspersoft, Endeca, and Tableau.

Information Builders. Is there anything about your BI products that is in any way technologically differentiated? If so, you might want to mention some examples to somebody some time.

Kalido. I’ve said this to you before, but it bears repeating — your positioning translates to “I-CASE for analytics,” and that’s not a good thing. If your product is not as cumbersome and entrapping as that sounds, you need to do a much better job of explaining why not.

SenSage. You are what you are. Sell out while the selling is good. You don’t have the corporate personality to make it into the analytic DBMS mainstream on your own.

Ingres. You need to be more engaged with analysts than you are. Ingres navel-gazed too much 25 years ago, and evidently you haven’t outgrown it yet.

TIBCO. You probably have a lot of cool analytic technology, but I don’t know of an influencer who has much relationship with or trust in you. Rethink how you’re approaching influencer relations top to bottom.

Tableau. You had a lot of mindshare, but it’s fading. Do something.

MarkLogic, graph DBMS vendors, etc. You’re clinging too hard to the NoSQL label. Nobody is out there deciding among Cassandra, neo4j, and MarkLogic. They might be deciding between MongoDB and MarkLogic, I guess, but if you admit to yourself that’s all it is you’ll probably change your messaging somewhat.

Objectivity. Get real about marketing. Infinite Graph is a cool opportunity. But I didn’t even ping you for a meeting when I’m in your area next week, because I wouldn’t have known who to reach out to.

Everybody (especially Objectivity). “First X deployed in the cloud” is almost surely an inaccurate claim. Don’t make it. And by the way, even if it were true, it probably wouldn’t be interesting.

• Neil Raden points out that business intelligence dashboards can be dangerously misleading. His reasoning (sound) is that whatever you measure is apt to be distorted by the fact people know they’re being measured. His solution (implied) is to hire a good-looking consultant like himself to do it right.
• I’ve had my issues with Fred Holahan, who was VP of Marketing when I posted that EnterpriseDB was not to be trusted. (That said, Fred is long gone from EnterpriseDB and my opinion hasn’t changed.) But he’s put up a good series of posts on the basis of the open source “progressive engagement” marketing funnel, including this gem on why you shouldn’t count on monetizing your community/free users.
• Oracle plans to increase its acquisition budget. The figure given is $70 billion over the next 5 years. Edit: But see this funny Register followup.
• Clayton Christensen wrote a phenomenal article on how to live a good life, from a very business-y perspective. (Only in one anecdote was it too religiously-oriented for my tastes.) Takeaways include:
  • Your core goals probably revolve around something other than business success. (E.g., family.) Don’t lose sight of that.
  • To the extent you’re a manager or leader, you may have a huge impact on other people’s lives. Use that power in admirable ways.
  • Teach people how to fish for answers, rather than just giving them answers. They’ll probably come to better conclusions than you would have anyway. (This is a core principle in my own consulting.)
  • Take time to reflect. And by the way, the same techniques you use for strategic analysis in business can be applied to your life as well.
• Mark Suster has a pretty good post expanding on my first Christensen takeaway, highlighting a point too often missing from articles in that genre: It’s not just family; it’s also all the cool things around us.
• I haven’t gone through the Hadoop Summit archives yet, but it looks as if there’s a lot of insight there about current Hadoop application activity.
• If you’re a cat lover and don’t hate simple/traditional music, check out Marc Gunn’s cat filksongs, especially the infectious “What Shall We Do With a Catnipped Kitty?” and “Lord of the Pounce”, both playable from the right sidebar of that page (#7 and #10 respectively). Gunn is also a chief perpetrator of the justly (in)famous Do Virgins Taste Better? cycle of filksongs.
• Former SAP exec Dennis Moore offers a theory as to why SAP cares so much about in-memory DBMS. It’s to integrate business processes, because SAP has no other software layer good at doing same. Interestingly, Dennis originated SAP’s previous attempt at meeting a similar need via its composite applications initiative. However, in Dennis’ view this benefit would only be achieved by a major rewrite of SAP’s applications.

Now a related can of worms has been opened in a related technology area — WordPress and WordPress themes. Since many bloggers use WordPress, this has gotten a lot of attention, and some interesting new insights have emerged.

Um, in case you didn’t know: WordPress is the software that runs blogs such as this, and it’s a GPLed open source project. However, the user interface — look, feel, and behavior alike — are determined by separate themes, that one usually gets from third parties (WordPress ships with a a few default choices).

It started when Matt Mullenweg went after the makers of an unfree theme Thesis, and wielding a legal opinion from the Software Freedom Law Center. The gist of the SFLC’s argument seems to be

They are derivative of WordPress because every part of them is determined by the content of the WordPress functions they call. As works of authorship, they are designed only to be combined with WordPress into a larger work.

And of course the point of the GPL is that if you create a derivative work of something GPLed, you have to GPL it yourself.

However, Perpetual Beta pointed out that, under the rules of copyright law as expressed in a court case known as Galoob, depending on another program does not make something a derivative work. This is actually blindingly obvious, as in the example of any program that runs on top of an operating system. Or for more examples see Dave Winer on the point.

Perpetual Beta further argued that, even if it were a derivative work, fair use would let one copy it anyway. I.e., if you’re engaging in “fair use,” you’re entitled to do what otherwise would be a copyright violation. Good point. The GPL license says in effect “You only are allowed to use this material (in certain ways) if you do as we say about your own work,” so that is defeated if the Fair Use Doctrine lets you say “Um, actually, I’m using this without your permission, so buzz off.”

GPL advocates can pontificate all they want about certain uses of GPLed code violating their license terms. But if either of these arguments holds up — and it looks to me like both do — a program that invokes GPLed code is not subject to the GPL just based on those invocations. And that, in turn, would more than imply that MySQL storage engine vendors could use GPLed MySQL-compatible front-ends without being under any GPL obligation themselves.

But other highlights of his column include:

• Some of those accounts are rather big-name. However, I’m not at all sure whether they’re actual production references.
• Andy Mendelsohn characterizes the sweet spot of Exadata’s market as “virtual private cloud.” That matches what Juan Loaiza told me six months ago.
• Oracle claims numerous competitive wins for Exadata. Let me hasten to note that one vendor’s “competitive win” is another vendor’s “our salesman read the deal as an unfavorable one and chose not to compete,” or even sometimes “Huh? We never heard about that deal.” That said, what I’m hearing is that Exadata is indeed a much stronger competitor than it used to be.
• Oracle claims a near $1 billion sales run rate for Exadata. No doubt, a large majority of those are hardware upgrades for existing Oracle database customers, often from non-Sun/Oracle hardware. Even so, some of those are surely deals that would have migrated away from Oracle in the pre-Exadata past.

*The comment threads are the most informative parts of those posts.

I’m a little unclear as to the Netezza Migrator details, not least because Netezza folks don’t seem to care too much about Netezza Migrator themselves. That said, the core ideas of Netezza Migrator are: 

• Netezza Migrator is an enhanced (?) version of EnterpriseDB’s Postgres Plus Advanced Server DBMS. (Recall that Postgres Plus is PostgreSQL-based and fairly Oracle-compatible.)
• Netezza Migrator does not run on Netezza appliances, but rather on conventional computers off to the side.
• Netezza Migrator generally farms out queries to Netezza appliances, but can also manage data itself. (That latter part could supposedly come in handy for small tables one might want to execute stored procedures against.)
• Netezza Migrator does a better job of farming out queries (and also inserts/updates/loads) to Netezza appliances than an Oracle DBMS would. The two biggest examples of that are:
  • Oracle will farm out SELECTs, but not JOINs.
  • Oracle won’t invoke Netezza’s parallel/bulk load capabilities.

• How quickly and cost-effectively does it execute SQL?
• What analytic functionality, SQL or otherwise, does it do a good job of executing?

And so, in undertaking such a selection, you need to start by addressing three issues:

• What does “speed” mean to you?
• What does “cost” mean to you?
• What analytic functionality do you need anyway?

Key elements of cost* include:

• Software license and maintenance
• Hardware purchase cost, maintenance, electric power, and computer room burden
• Database and system administration
• (For some uses cases) Programming

*Assuming a classical in-house IT shop, where products are typically bought rather than leased/rented. With outsourced and/or monthly-fee structures, the details change but the principles remain the same.

Most of that can be evaluated pretty well via a spreadsheet, although things can get a bit tricky when you get to people costs, which are a large fraction of the whole. In particular, different analytic DBMS product suites have great, high-performance support for different (and often rapidly growing) sets of functionality – basic and advanced SQL, statistics, and more. Figuring out which ones will be best for your programmers, and how significant the differences are — well, that’s a lot like any other programming language evaluation, and those are rarely neat or clean-cut.

But when it comes to evaluating speed, there’s no substitute for a well-designed proof of concept (POC). Many analytic DBMS and appliance vendors are happy to let you do a POC, on your own premises (or remotely if you prefer), under your control, at no cost to you. And that’s great. It is crucial that a POC be run either by you, by a consultant* answerable to you, or – if you decide the vendor must run it for you – at least with you watching every step of the way and knowing exactly what is being done. Appliance vendors do find it cheaper to run POCs on their own premises, so a certain reluctance to ship you a box is understandable. But make no compromises about the transparency of a POC, or about your control of exactly what it is that gets tested.

*Since I sell consulting services for users evaluating analytic DBMS, I naturally am biased to think that consultants can be very useful in the process. But whether you should use them a little (sanity check), a medium amount (work with you through the process), or heavily (actually drive the process for you and/or execute the POCs) is very dependent upon your specific situation.

So far as I’ve been able to tell:

• Netezza loves to ship boxes to prospects for POCs, and have them set up the boxes and do POCs themselves. That’s a big reason why Netezza wants to call attention to this subject.
• Oracle has generally been pretty reluctant to ship Exadata boxes out for POCs. That’s the other reason Netezza wants to call attention to the issue.
• Open source vendors make it easy for you to download and test at least their community editions.
• Vertica makes it pretty easy for you to test its software too (download or cloud).
• ParAccel has generally insisted on running POCs itself, although it will do so on your premises if you insist.
• Teradata naturally tries to do POCs on its own premises, but doesn’t insist too hard. (Edit: Randy Lea of Teradata says that Teradata is now doing over half its POCs onsite.)
  

Most of the criticisms I’ve heard of vendors’ POC practices have been directed at Oracle or ParAccel.

For most POCs, it’s a good conceptual template to form and then test a hypothesis to the effect of:

• For a given technology product assemblage (brand of DBMS, number of nodes, etc.), and
• For a given level of human effort (e.g., administrative effort), you can
• Run a given a workload, with
• Satisfactory and satisfactorily consistent response times

Sometimes absolute throughput and price/performance are important secondary considerations; sometimes they’re less germane. But either way, it’s almost always right to focus primarily on the questions of “What do I want this system to do?” and “What do I think we’re going to have to invest in it?” By way of contrast, it’s often misleading to focus too much on questions like “What’s the one number that best describes the performance of this system?” — even if you customize that calculation for your environment – or, even worse, “How much speed-up can I get on my single worst Query from Hell?”

The fundamental rule of POC construction is: Model your entire use case as best you can. That means you need to consider, at a minimum:

• Your whole concurrent query, other analytic, and low-latency update workload (peak).
• Your whole query, analytic, load, backup, and maintenance workload (ongoing).
• Partial-failure scenarios.
• Your core SLAs (Service-Level Agreements).

Of course, that’s not as easy as it sounds. Presumably, the main reason you’re getting a new analytic DBMS is that you want to do new kinds of analysis. By the very nature of analytics, you won’t know what analytic operations are most useful until you try them out and see what their results are. On the other hand – if you haven’t done considerable thinking about how you’re going to use your new analytic database, how did you ever get funding for the project in the first place?

Seriously, I could write multiple posts, each as long as this one (but more application-oriented), about how to upgrade your analytic capabilities (and which fool’s gold to avoid). But this has gotten pretty long already, so for now I’ll just stop here.

Note: My clients at Netezza asked me to write something short about POCs they could use as a kind of foreword to some collateral, where by “short” they meant single-paragraph or something like that. They’re great clients, so I said yes, under the condition I could also use it as a blog post. Except … this post didn’t turn out to be nearly as short as they envisioned. Oops.

Related links

• My February, 2009 slide deck on how to select an analytic DBMS is in many parts still pretty current

And it’s not going to get any better. Next week = the oft-postponed elder care trip. Then I’m back for a short week. Then I’m off on my quarterly visit to the SF area. Soon thereafter I’ve have a lot to do in connection with Enzee Universe. And at that point another month will have gone by.

Anyhow:

• Back in January, Oracle finally briefed me on Exadata 2. I also requested and got permission to post what I regarded as pretty interesting slides, then never got around to doing so. Well, here they are. (Pay no attention to the word “Confidential”.)
• Two people I have a lot of respect for, Cindi Howson and Doug Henschen, seem bullish on SAP’s in-memory NewDB efforts. But for a variety of execution reasons, I’m skeptical that this will matter for anything except SAP’s analytics suite. I.e., I don’t think anybody much except SAP will write OLTP apps to it, and I don’t think that without OLTP apps being written to it it’s much more than Business Objects’ answer to QlikView.
• I just learned that Netezza’s previous geospatial technology didn’t get ported to TwinFin. However, Netezza obviously found a geospatial alternative.

I ‘m beginning to make a habit of asking vendors for a postable version of their slide decks. Sybase IQ is another example.

• Google is doing something called BigQuery that is “SQL-like” for big data analytics. I don’t know anything about it.
• I also don’t know anything about IBM BigSheets yet. It sounds something like Datameer, but that could be way off the mark.

• ITA Software builds huge OLTP systems that it runs itself on behalf of airlines.
• Very, very unusually, ITA Software builds these huge OLTP systems in LISP.
• ITA Software is an Oracle shop (see Dan Weinreb’s comment).
• ITA Software is run by a techie (again, see Dan Weinreb’s comment).
• ITA Software has an interesting screen-scraping/web ETL project called Needlebase

ITA’s software does both price/reservation lookup/checking and reservation-making. I’ve had trouble keeping it straight, but I think the lookup is ITA’s actual business, and the reservation-making is ITA’s Next Big Thing. This is one of the ultimate federated-transaction-processing applications, because it involves coordinating huge OLTP systems run, in some cases, by companies that are bitter competitors with each other. Network latencies have to allow for intercontinental travel of the data itself.

Indeed, airline reservation systems are pretty much the OLTP ultimate in themselves. As the story goes, transaction monitors were pretty much invented for airline reservation systems in the 1960s.

A really small project for ITA Software is Needlebase. I stopped by ITA to look at Needlebase in January, and what it is is a very smart and hence interesting screen-scraping system. The idea is people publish database information to the web, and you may want to look at their web pages and recover the database records it is based on. Applications of this to the airline industry, which has 100s of 1000s of price changes per day — and I may be too low by one or two orders of magnitude when I say that — should be fairly obvious. ITA Software has aspirations of applying Needlebase to other sectors as well, or more precisely having users who do so. Last I looked, ITA hadn’t put significant resources behind stimulating Needlebase adoption — but Google might well change that.

Edit: I just re-found an old characterization of (some of) what ITA Software does by — who else? — Dan Weinreb:

I am working on our new product, an airline reservation system.  It’s an online transaction-processing system that must be up 99.99% of the time, maintaining maximum response time (e.g. on www.aircanada.com).  It’s a very, very complicated system.  The presentation layer is written in Java using conventional techniques.  The business rule layer is written in Common Lisp; about 500,000 lines of code (plus another 100,000 or so of open source libraries).  The database layer is Oracle RAC.  We operate our own data centers, some here in Massachusetts and a disaster-recovery site in Canada (separate power grid).

Related links

• ITA Software and Needlebase websites
• More about LISP

• The X Company (XCo) has a <1 TB database.
• 100s of XCo’s customers log in at once to run reports. 50-200 concurrent queries is a good target number.
• XCo had been “suffering” with Oracle and wanted to upgrade.
• XCo didn’t have a lot of money to spend. Netezza pulled out of the sales cycle early due to budget (and this was recently enough that Netezza Skimmer could have been bid).
• Greenplum didn’t offer any references that approached the desired number of concurrent users.
• Ultimately the evaluation came down to Vertica and ParAccel.
• Vertica won.

Notes on the Vertica vs. ParAccel selection include:

• ParAccel sent an engineer on-site to do a proof-of-concept (POC), and generally competed very hard for the deal.
• Vertica dropped by for a sales call once, and let XCo do the Vertica POC itself.
• Not surprisingly, XCo got the impression that Vertica was easier to set up and administer than ParAccel.
• Also, when ParAccel emphasized architectural features such as custom “backplane” and compiled queries, XCo got the impression – right or wrong – that ParAccel’s performance was more brittle or situational than Vertica’s.
• ParAccel was modestly faster than Vertica in the POC. (I think — Vertica’s numbers were described as being “very competitive.”)
• In multiple ways, Vertica gave the impression of greater product and vendor maturity than ParAccel.

My contact continues to be interested in all things Greenplum, and has recommended Greenplum Single-Node Edition to his analyst colleagues.