• 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.

This piqued my interest, so — recalling that ANTs is a public company — I decided to take a look at just how successful their software products business is. Well, for the quarter ended March 31, 2010, ANTs’ 10-Q filing says (emphasis mine): 

The Company’s revenues for the three months ended March 31, 2010 and 2009 include service revenues representing managed and professional service fees for database and network maintenance and support services. Revenues for the three months ended March 31, 2010 were $1.5 million, an increase of $0.1 million compared to $1.4 million for the three months ended March 31, 2009.  For the three months ended March 31, 2010, two customers accounted for 96% of the Company’s gross revenues (Company A, 72% and Company B, 24%) compared to three customers that accounted for 97% of the Company’s gross revenues for the three months ended March 31, 2009 (Company A, 57%, Company B, 29% and Company C, 10%). The increase in revenues for the three months ended March 31, 2010 over the comparable period in 2009 is primarily attributable to professional service projects for Company A that were initiated during or subsequent to the three months ended March 31, 2009, partially offset by professional service projects for Company B and Company C that were completed subsequent to March 31, 2009.

Conditional on the Company’s technology developments being successful, the presence of customer demand and the Company having a competitive advantage, future revenues may include sales and licenses of its ANTs Compatibility Server (“ACS”) product and managed services revenue related to existing and new contracts and professional services revenue from pre- and post-sales consulting related to ACS and other database consolidation technologies. Sales of the Company’s first ACS product, which translates from Sybase to Oracle, have been limited due to the structure of the sales arrangement and go-to-market strategy. As such, the Company has structured the go-to-market strategy for the second ACS product differently via the use of an Original Equipment Manufacturer (“OEM”) agreement. Pursuant to the OEM agreement, ANTs is responsible for technology development specifically tailored to the OEM’s needs. The OEM will assume responsibility for marketing, sales and support of the technology on a worldwide basis, while ANTs will be the preferred service provider for migration projects. The Company is currently in the process of developing the second ACS product for a planned announcement and release in mid-2010. The Company intends to develop additional ACS products based on market demand and the availability of resources for development.

In other words, as of four months ago ANTs had had $0 in business in what it says is its main product area, which is pretty much the range the company has been in throughout its complicated history.  Kozak’s post did link to a claim that IBM has experienced over 300 migrations to DB2. However, that figure includes Oracle-to-DB2 migrations that having nothing to do with ANTs. And by the way, IBM’s migration strategy is focused largely on ISVs, so the whole Sybase-ANTs dust-up may be about a type of business (direct capture by DB2 of Sybase ASE enterprise customers) nobody’s sales force is seriously pursuing.

True, the Sybase-to-DB2 emulation technology hadn’t been released as of then. Even so, I think it’s a wee bit early for ANTs to be acting as if there’s been any proof it ever has had or will have any significant market success.

The first two things to understand about SQL Anywhere is that there actually are three products:

• Sybase SQL Anywhere, a mid-range relational DBMS.
• Sybase UltraLite, a DBMS for mobile devices.
• Sybase MobiLink, a replication/sync tool.

and also that there are three main deployment/use cases:

• Generic desktop or server computers. This was the original market for SQL Anywhere.
• Laptop/handheld computers. This was the original growth market for SQL Anywhere. In particular, Siebel Systems’ first growth spurt was selling sales force automation software on laptop computers with SQL Anywhere underneath.
• Specialized devices. Earlier this decade, Sybase thought SQL Anywhere’s big growth market was on specialized devices. (I recall a video featuring some kind of automated pill dispensing machine for hospitals.)

Meanwhile, terminological weirdness includes:

• At various times the product Sybase SQL Anywhere has had “Server” in its name, but that seems not be part of the naming convention at the moment. Sybase folks still talk about it that way, however.
• Is SQL Anywhere a product? A group of products? A division? Again, that depends on whom and when you ask.
• When Sybase speaks of SQL Anywhere being in the “embedded” database market, it’s talking of any OEM business, not just deployment on particular kinds of devices. (IDC has long used that confusing terminology, which is a regrettably good excuse for vendors to use it as well.)

I get the impression that there are two big markets for the Sybase SQL Anywhere family:

• ~1000 OEM partners for Sybase SQL Anywhere. Notable examples include:
  • Intuit (for QuickBooks)
  • Symantec (for NetBackup)
  • Sybase IQ, if you want to view it that way (a lot of Sybase IQ’s front-end is actually SQL Anywhere code)
• Direct enterprise customers for mobility-oriented combinations of Sybase UltraLite, Sybase SQL Anywhere, and Sybase MobiLink. Notable examples include:
  • Pepsi Bottling Group (repairmen, using handheld devices)
  • US 2010 Census (140,000 people address checkers – every address in the US was checked against GPS coordinates, it seems)

By way of contrast, the market for true embedded systems never took off as strongly for Sybase SQL Anywhere as it did for, say, pre-acquisition solidDB. Added together, this all seems to amount to ~ 10 million users overall, as per a slide deck Sybase graciously gave me permission to post.

Other market notes include:

• Sybase says that the main competitors for Sybase SQL Anywhere are Microsoft SQL Server, Oracle, and occasionally MySQL, with Progress coming up only rarely. I would have thought Progress OpenEdge RDBMS would be higher on the list (simple DBMS for the OEM market) – but come to think of it, it’s been quite a while since I’ve run into anybody who says they compete much with Progress OpenEdge. Perhaps Progress just isn’t selling its core product very hard these days.
• 80-90% of Sybase SQL Anywhere installations are on Windows, but the fact that SQL Anywhere also runs on Macintosh and ‘nix platforms is apparently pretty important to sales.
• The main platforms for Sybase UltraLite are Blackberry and Windows Mobile, although with iPhone support newly added in SQL Anywhere Version 12, that’s a good bet to change.

Besides the above, the key points about Sybase SQL Anywhere are:

• Sybase SQL Anywhere is designed for a no-DBA, “customers may not know there’s a DBMS” there kind of easy administration. (That’s one reason I compared it to Progress.)
• Sybase SQL Anywhere has a reasonable set of mid-range DBMS features, including:
  • Triggers
  • Stored procedures
  • Referential integrity
  • Geospatial datatype
  • Text datatype (with a CONTAINS clause), and you can index external documents
  • Multiprocessor/multicore operation

Sybase SQL Anywhere Version 12 seems to have a variety of performance improvements, of which the most interesting are:

• If you’re using an ORM (Object-Relational Mapping) layer such as Hibernate, the SQL Anywhere optimizer now works hard to rewrite some of the horrific SQL that can be generated, for example by flattening or eliminating a lot of subselects.
  • There’s also a “Hibernate dialect” of SQL Anywhere – I’m not sure what that means, but it clearly indicates that SQL Anywhere wants to be Hibernate-friendly.
• When the SQL Anywhere optimizer decides the statistics are wrong, it reruns them, piggybacking on a subsequent query if it can, doing a background job if it must. Somewhat pretentiously, Sybase refers to this as “self-healing statistics”.

Many SQL Anywhere features are of course missing in Sybase UltraLite, but geospatial datatypes are present.

Finally, it’s a natural conjecture that MobiLink is related to Sybase Replication Server – but that conjecture turns out to be wrong. That said, keeping Sybase’s various replication offerings straight is tricky.

• Slide 2 has some market success figures and so on. (>3100 copies at >1800 users, >200 sales last year)
• Slides 6-11 give more detail on Sybase’s indexing and data access methods than I put into my recent technical basics of Sybase IQ post.
• Slide 16 reminds us that in-database data mining is quite competitive with what SAS has actually delivered with its DBMS partners, even if it doesn’t have the nice architectural approach of Aster or Netezza. (I.e., Sybase IQ’s more-than-SQL advanced analytics story relies on C++ UDFs  — User Defined Functions — running in-process with the DBMS.) In particular, there’s a data mining/predictive analytics library — modeling and scoring both — licensed from a small third party.
• A number of the other later slides also have quite a bit of technical crunch. (More on some of those points below too.)

Sybase IQ may have a bit of a funky architecture (e.g., no MPP), but the age of the product and the substantial revenue it generates have allowed Sybase to put in a bunch of product features that newer vendors haven’t gotten around to yet.

More recently, Sybase volunteered permission for me to preannounce Sybase IQ Version 15.2 by a few days (it’s scheduled to come out this week). Sybase IQ seems to be focused on large part on the government/intelligent market, with three major features being:

• A kind of data federation, querying external databases, that makes sense mainly in the context of rigorous security rules. (I find that confusing, since Sybase IQ’s indexes tend to hold all the information in the database, but I didn’t push the point.)
• An upgrade to Sybase IQ’s built-in text indexing. I doubt anybody would confuse this with best-of-breed text search, but evidently that intelligence community is satisfied with less. But even before 15.2, Sybase IQ could do both LIKE and WHERE CONTAINS searching.
• Improved LOB (Large OBject) management.

One part of my Sybase IQ conversations I haven’t blogged yet in much details is scale-out, concurrency, and “multiplexing.”

• Sybase feels that Sybase IQ’s competitive sweet spot, especially in terms of performance, is reached when there are 20 or more concurrent queries.
• In general, Sybase asserts that a shared-everything architecture is great for concurrency — just run different queries on different boxes, all against the same data.
• The ability to use a bunch of boxes run Sybase IQ is called “multiplexing.”  This is a chargeable option, without which one is limited to a single SMP box.
• Just under 20% of the top 250 Sybase IQ customers have multi-node scale-out configuration (vs. single-node SMP scale-up). And around 8% have it overall.
• Sybase IQ nodes can be heterogeneous (e.g., in compute power).
• Sybase IQ nodes can be dedicated to be read-only, or can be read-write. Indeed, Sybase IQ nodes can change roles dynamically, for example becoming write-only during nightly batch load. (I didn’t clarify whether all this applies just to nodes-as-boxes, or if some parts apply to specific processors or cores within the same box.)
• Sybase noted that data mart outsourcers can offer differentiated SLAs (Service Level Agreements) depending upon which nodes they give which customers access to.
• Most Sybase IQ installations start at 8 cores or more. The Sybase IQ Small Business Edition, limited to 4 cores, is not a big seller.
• Sybase IQ has a straightforward round-robin load-balancing story via third-party technology.

Finally, along the way in the discussions I picked up various tidbits about the Sybase IQ user base. Unfortunately, Sybase is pretty vague in discussing database sizes — are they user data? Are they compressed? What do the numbers mean? With that huge caveat:

• By some metric or other, a couple of classified customers are approaching petabyte scale.
• The largest commercial Sybase IQ customer — a credit card company — has a couple hundred terabytes or so.
• The largest financial services Sybase IQ databases are 50-70 terabytes. This sounds low, frankly, so maybe those are compressed figures, with user data being 200+ terabytes. But I’m just speculating there.
• Sybase IQ has a little less than 100 customers in the “data aggregator” market, which is a lot like what I call “data mart outsourcer.”
• Sybase IQ’s ILM technology is a chargeable option, with Sybase being “cautious” about sales. Compliance is a big market driver for it.
• Sybase IQ’s #1 vertical market is financial services. Other biggies are government, telecom, marketing services, and to some extent retail.
• As of February, there were 40-45 production users of Sybase IQ 15.0 and 15.1.

For starters, Sybase IQ is not just a bitmapped system, but it’s also not all that closely akin to C-Store or Vertica. In particular,

• Sybase IQ stores data in columns – like, for example, Vertica.
• Sybase IQ relies on indexes to retrieve data – unlike, for example, Vertica, in which the column pretty much is the index.
• However, columns themselves can be used as indexes in the usual Vertica-like way.
• Most of Sybase IQ’s indexes are bitmaps, or a lot like bitmaps, ala’ the original IQ product.
• Some of Sybase IQ’s indexes are not at all like bitmaps, but more like B-trees.
• In general, Sybase recommends that you put multiple indexes on each column because — what the heck – each one of them is pretty small. (In particular, the bitmap-like indexes are highly compressible.) Together, indexes tend to take up <10% of Sybase IQ storage space.

Sybase IQ is not immune to Sybase’s confusing choices in version numbering. Thus:

• Sybase IQ Version 15.2 will be announced and released soon.
• Sybase IQ Version 15.1 was a set of “binary replacements” rather than an “upgrade release” for Sybase IQ Version 15.0.
• Sybase IQ Version 15.0 was launched in February, 2009 and released for general availability some time thereafter.
• The prior version of Sybase IQ was 12.7.
• GA isn’t always GA, and some language localizations and so on weren’t ready for a while. Consequently, a lot of Sybase IQ sales continued to be of Version 12.7 even in the second half of 2009.

Now let’s get down to some technical particulars.

Sybase IQ columns are always stored in RowID order. However, RowIDs are logical and not physical, and hence take up little disk space. A small amount of per-page metadata lets you find the specific cell you want. (Cells are commonly fixed-width, in which case finding the cell of choice is a simple calculation.) So RowIDs are not much of an I/O overhead issue, although I’m not sure at what point they get unpacked and start needing to be carried around as the data travels through silicon.

Sybase IQ has 9 or so kinds of indexes. The choice of index has a lot to do with cardinality. In the extreme low-cardinality case, a simple bitmap might do. With intermediate cardinality, you might go to a modified kind of bitmap – e.g., if there there are 2^16 possible values, you can represent a value in 16 bits, and bitmap operations are approximately 16 times as costly as if the number of possible values were only 2^1. For very high cardinality, there’s a B-tree-like index called “High Group”.

Note: Surely every Sybase index name, at some time, made sense to at least one engineer.

Sybase IQ’s execution engine does seem to rely quite a bit on bitmaps. E.g., intermediate query results are stored as bitmaps, which helps them play nicely with each other and with many of the indexes. Sybase claims that Sybase IQ’s bitmap orientation often makes WHERE clauses execute very quickly. Sybase IQ reoptimizes queries after WHERE clauses are evaluated. Complex expressions are, when possible, evaluated once per unique value, not once per row.

Speaking of unique values – Sybase IQ’s compression story doesn’t currently match that of some other columnar products, but it seems to stack up pretty well against row-based systems. In particular:

• Sybase says IQ compression is most commonly 50-70%.
• Sybase further says that, in most cases, compression falls into the range 40-85%.
• Page-level LZ compression is decompressed upon read (duh).
• Dictionary/token compression may be decompressed later. For example, GROUP BYs are commonly done on tokens, and JOINs sometimes are.

Sybase IQ boasts pipelining, in two senses. First, IQ tries to read pages for multiple queries at the same time. Second, Sybase IQ tries to prefetch pages into cache before they’re needed. Sybase points out that these prefetched pages have the WHERE clauses already executed, and that no extra baggage is being dragged into cache that doesn’t need to be there.

Highlights of Sybase IQ’s update and load story include:

• Sybase IQ is optimized for large bulk loads. No surprise there.
• Sybase IQ has several options for microbatching and/or trickle feeds.
  • The coolest is Sybase RAP.
  • More generally, microbatching is based on Change Data Capture. Sybase has various ETL/replication technologies, creating a confusing array of options in that regard.
  • Sybase says that one customer is microbatching 1000s of rows with 1 minute latency.
• There’s something about snapshotting and hence loads not interfering with queries. I’m not clear on the details.
• Assuming you have enough parallelism, you can dedicate some nodes to queries while others are dedicated to load. (Recall that Sybase IQ is shared-disk.)

I’ve lost track a little bit as to which “advanced analytics” functionality is in Sybase IQ 15.1, which will be in 15.2, and what’s a future beyond that, which is a great excuse for me to leave it out of what has already become a rather long post. But anyhow, except perhaps for the future stuff and/or some time series functionality, none of it seems terribly advanced. Sybase IQ does have two stored procedure languages, namely the ones for Sybase ASE (T-SQL) and for Sybase Anywhere or Adaptive Server Anywhere or whatever it’s called this week (Watcom SQL, which Sybase asserts is similar to the ANSI SQL stored procedure language).

Similarly, I’ll leave a lot of other stuff out as well, and for now stop here.

Related links

• I haven’t repeated every detail here from my August, 2009 technical post about Sybase IQ
• And here’s more about Sybase IQ, including some Sybase IQ 15.2 features, some market penetration info, and a slide deck

That said,  

• Raj said that Sybase’s Aleri acquisition was, if anything, tracking ahead of expectations.
• Raj didn’t seem the slightest bit focused on the Coral8/Aleri CEP-based BI strategy that John Morell had long championed.
• Raj reminded me that Sybase SQL Anywhere has numerous OEMs, not just on the true desktop/laptop or smaller, but also in a return to its server/workgroup roots. Sybase SQL Anywhere even added geospatial indexing recently.

Raj also spoke glowingly of SAP’s in-memory database technology and the potential for Sybase of same — until I asked a follow-up question. At that point, he confessed that he didn’t really know much about about SAP’s in-memory database technology yet. As I said before, I believe SAP is fairly sincere about its belief that its in-memory database technology will conquer the world — but this is a naive and poorly-founded opinion even so.

One tidbit I did get is that SAP’s in-memory database technology is not just son-of-T-REX. A Korean (Raj thinks) company SAP had acquired is also in the mix. Raj also had the impression SAP’s in-memory technology can do rows, columns, or hybrid structures. On the one hand, that makes sense. On the other, it’s not a perfect fit with what Hasso Plattner said last year.

• Sybase’s main businesses are:
  • Classic OLTP DBMS (Sybase ASE, for Adapative Server Enterprise, unless I’ve missed yet another name change).
  • Analytic technology — mainly Sybase IQ, but more generally Sybase RAP.
  • Mobile technology. (The frequently renamed small DBMS SQL Anywhere was the foundational product of and still is included in the mobile division.)
• SAP’s thoughts on in-memory database management are interesting. However, I think SAP’s oft-repeated claim that it has a lot of important in-memory database technology to bring to Sybase (or for that matter SAP customers) is mainly smoke and mirrors. Cool data access methods, good niche database products, and broadly applicable multi-domain DBMS innovations are three different things. Granting that SAP probably has the first and thinks it has the second is not the same as giving it much credence for having the third.
• SAP claims that, 15 years after its refusal to support Sybase turned Sybase into a DBMS also-ran, it by now is “relatively simple” to port SAP’s apps to Sybase ASE, and that they will make that happen. I actually believe that SAP’s apps will soon run on Sybase ASE, where by “soon” I mean “in a couple of years for no-apologies general availability.” (Certifying a DBMS for SAP is a long process.) The main missing features — e.g., row-level locking — were already put into Sybase back in the last millenium. Nor could there be fundamental architectural problems that keep SAP from supporting Sybase ASE, or else SAP couldn’t have supported Microsoft SQL Server (which, long ago, was a Sybase fork).
• I don’t see any market or competitive dynamics that would lead the SAP acquisition to hurt Sybase’s ASE or mobile businesses. General merger management mishegas is, of course, always a possibility.
• SAP Business Objects partners with Sybase IQ’s competitors. That could be a problem. However, coopetition is pretty strong in the business intelligence market. I don’t think any of SAP Business Objects, IBM Cognos, or Oracle Business Intelligence are much held back from partnering by competitive dislike of their parent companies.
• The rest of SAP might be able to drum up some extra business for Sybase IQ.
• It would be natural for IBM/Cognos to now buy a columnar DBMS of its own. Vertica is an obvious first choice. ParAccel would surely come much cheaper. Since ParAccel has little chance of surviving as an independent company — too immature and too little differentiation to overcome that — I’d expect ParAccel’s board to jump at the chance to sell out.
• It would be interesting if SAP Business Objects would revive the CEP-based BI idea.
• I gather Sybase’s AnswersAnywhere concept network/object model-based natural language/speech recognition technology never went anywhere. Unsurprising (it seemed like it needed too much hand-building to scale semantically), but regrettable even so.
• I don’t see anything in this acquisition that would revive PowerBuilder (Sybase’s Visual Basic competitor), Sybase’s CASE (Computer-Aided Software Engineering) tools, and so on.
• And on the personal side — I’ll probably lose Sybase as a customer due to this merger, but it could have been worse. A lot of vendors smaller than Sybase are bigger customers for Monash Research.

Edit: Right after I posted this, I saw email from Sybase clarifying that Sybase’s in-memory technology, while slightly influenced by some ANTs IP Sybase bought non-exclusive rights to, is essentially home-grown. That’s what I thought, but the call sounded like it was saying something different.

Further coverage of SAP/Sybase:

• SAP believes in database proliferation
• More quick reactions to SAP/Sybase
• Technical basics of Sybase IQ
  

• Vertica had a “killer” Q4 and is doing very well in Q1 again.
• Vertica burned hardly any cash last year; i.e., it was close to cash-flow neutral in 2009.
• Vertica is hiring aggressively, e.g., in sales.
• Vertica is well down the path with several CEO candidates who Jerry regards as outstanding. He is hopeful there will be a new CEO in April. (But I bet that would be late April, given what Jerry mentioned about his own travel plans.)
• Absent a full-time CEO, Jerry and Andy Palmer are spending a lot more time with Vertica.
• One Vertica customer is approaching a petabyte of user data. The last time Vertica had checked, that customer had been more in the ¼ petabyte range.
• Other multi-hundred terabyte Vertica databases were mentioned, including one where Vertica claims to have beaten Teradata and perhaps other competitors in a head-to-head competition (it sounds like that one’s too recent to be deployed yet).
• Vertica sees Aster and Greenplum competitively more often than it sees ParAccel.
• Vertica sees Sybase IQ competitively a lot in financial services (in new-name accounts for Sybase as well as where some kind of Sybase DBMS is an incumbent), and more occasionally in other sectors.

NDA parts of the conversation also gave me the impression that Vertica is moving forward just as eagerly as its peers. I.e., I didn’t uncover any reason to think that Ralph’s departure is a sign of trouble, of the company being shopped, etc.

On the other hand, I didn’t uncover any other clear reason for Ralph’s departure either. The party line is that Ralph left for “personal reasons”. It was his decision to leave. He did a great job while at Vertica. Basically, Vertica is saying that, even though all was going swimmingly, Ralph just up and quit, leaving some very valuable unvested stock options on the table at what had been his first CEO gig ever.

Contacting Ralph didn’t add any immediate insight. He responded quickly via a Twitter DM, but was in the airport for a trip to his home country of South Africa, and deferred discussion until after his return.

Incidentally, Infobright and ParAccel have both also had recent CEO turnover. Stated reasons in each case were of the “Right person to lead the next stage of the company’s growth” variety.

• One of the most confusing things about Sybase ASE is its version numbering. In particular,
  • Sybase ASE 15.5 went GA in December, 2009. (But the clustered version is just coming out in March.)
  • The prior version of Sybase ASE was 15.03.
  • Sybase ASE 15.0 came out in September, 2005.
  • The version of Sybase ASE before that was 12.5.
  • And by the way, Sybase System 10 came out in 1994 or so.
• Sybase ASE 15.0 was a major rewrite. In particular, Sybase ASE 15.0 had a “brand new” optimizer and query processing engine, based on the Volcano model. The main driver of the rewrite was to make Sybase ASE suitable for mixing OLTP and some level of decision-support workloads. (Not on the order of what Sybase IQ can handle, but at least operational reporting and so on.)
• I haven’t looked up Volcano in more detail than to confirm that what I thought Raj said made sense, but as he characterized it, it’s a lot more modular than what Sybase had in ASE 12.5. For example, substantially the only join algorithm in Sybase ASE 12.5 was nested loop – no hash or sort/merge.
• As you might imagine, a lot of things one might regard as core modern DBMS features were only added to Sybase ASE once 15.0 came out. Examples include:
  • Various forms of partitioning at the storage level.
  • User-defined functions (UDFs).
  • A clustering offering that competes with Oracle RAC. (100 or so customers are on that so far.) Absent clustering, Sybase ASE is limited to a single SMP (Symmetric Multiprocessing) box.
  • Shared disk. Amazingly, it seems that before 2008, every node in an SMP box running Sybase ASE had its own private partition (maybe not the right word) of data.
• In Sybase ASE, you have lots of databases managed by one database server. You can write SQL statements that span multiple databases, but they have to reference database names as well as table names.
• There are several ways to get data from one place to another in Sybase’s technology and nomenclature, specifically including Replication Server, Incremental Data Transfer, and “proxy tables.” (Other than the fact that Replication Server is a separate, chargeable product, I don’t really have these straight.) In addition, there’s a hand-coded one in Sybase RAP, which will get a planned 5-6X performance improvement later this year when it is replaced by Incremental Data Transfer.

And in what basically sounds like a very cool approach, Sybase ASE has a lot of memory-centric aspects. That said, Sybase’s in-memory ASE story is still incomplete (wait until the next release) and confused (I think in part because of what’s missing in the current release).  Also, this is one area where the non-technical nature of the briefing got in my way. So here’s some of what I do and don’t know about Sybase’s memory-centric ASE strategy:

• Sybase lets you mix and match on-disk and in-memory databases under one instance of Sybase ASE. To a programmer, it all looks like ASE.
• I don’t know exactly what the limitations are on what you can do with in-memory databases, how you can use them in tandem with on-disk databases, etc.
• You can replicate data from disk to an in-memory Sybase ASE database today. (Hello caching, ala Oracle Times Ten or IBM DB2/solidDB.)
• Replicating from memory to disk is a near-term future capability. (So Sybase does not yet have a hybrid memory-centric story ala solidDB Classic.)
• I have no clue as to what kinds of in-memory data structures Sybase ASE uses.

*Links to Gartner Magic Quadrants commonly break, but that one worked at the time of this posting.

• Gartner thinks that data warehouse appliances are on the rise, due to their simplicity.
• Gartner correctly says that Teradata has been a data warehouse appliance vendor from the getgo.
• Gartner characterizes IBM as being an appliance vendor as well.
• Gartner suggests that HP is having trouble living up to its technical promises for Neoview.
• Gartner further suggests — no surprise here — that HP Neoview has had very few new customers past its initial wave.
• Gartner notes IBM’s difficulties in selling data warehouse installations of DB2, despite what on paper is great-sounding technology.
• Gartner says — also no surprise — that illuminate “has seen little success in North America since opening its first office in the U.S. over two years ago.”
• Ingres has evidently gotten a few BI-centric “appliance” deals, e.g. with Jaspersoft. But basically Ingres isn’t doing well in data warehousing.
• Gartner does say Ingres has “the strongest open-source DBMS offering for data warehousing.” Being very literal about “open source,” that’s a defensible claim — but it’s pretty irrelevant in a world where Greenplum Single-Node Edition can be had for free. It also waves away all the data mart use cases in which Infobright Community Edition shines.
• Gartner says that Netezza is working out as a “complex workload” enterprise data warehouse provider, according to reference checks, in addition to its established success in data mart scenarios.
• Gartner says Oracle’s offering has finally become “accepted” in the market for databases >50 TB. I guess I can live with that fairly weak claim, but I wouldn’t go much further than that.
• Gartner asserts that, unlike software-only Oracle, Oracle Exadata isn’t significantly harder to administer than “other mixed OLTP/OLAP DBMS vendors,” because Exadata is fast enough you don’t need to jump through all those hoops any more to get tolerable performance. The money quote is “one reference reported reducing the number of indexes by a factor of 100 to fewer than five.” Note, however, that Gartner does not seem to assert that Exadata’s ease of use rivals that of the newer analytic DBMS specialists.
• Gartner confirms Oracle’s reluctance to do onsite Exadata POCs, but says it is not absolute. This is roughly compatible with what I’m hearing elsewhere, and indeed with Oracle own claims to be ramping up availability of Exadata POC hardware.
• Gartner’s criteria for inclusion include at least 10 different organizations having a product “in production.” Thus, the big surprise was ParAccel being included. The money quote there is “With approximately 20 customers in the pharmaceutical, retail, financial and media/advertising analytics sectors, ParAccel has a good reference base.” That assessment is difficult to reconcile with other information, but I’ve been told Gartner is sticking to its guns. That assessment would be even harder to believe if those 20 references were all alleged to be true production customers.
• Gartner notes that you basically can’t run a 1 TB+ MySQL data warehouse without sharding. (Of course, Infobright has an alternative, and up to a small number of terabytes so does Kickfire.)
• Gartner reports that at least some customers are pleased with Sybase IQ’s mixed workload/enterprise data warehouse capabilities.
• Gartner correctly notes that Oracle Exadata is a price-competition challenge for Teradata.
• Gartner notes that 20% of Vertica’s customers are outside the US. While not shocking, that’s more than I realized.
• Gartner notes something I don’t think I’ve posted yet, which is that Vertica has a customer with 300 TB of data. (The identity is a deep dark secret, but if I told you you probably wouldn’t recognize the name anyway.)

As does any such piece, the Gartner Data Warehouse DBMS Magic Quadrant also has outright errors.  For example:

• Aster Data isn’t really “the newest entrant to the DBMS data warehouse world.”
• Aster’s SQL/MapReduce was not new in Release 4.0.
• Greenplum isn’t yet pushing down code to the storage tier.
• I’m not sure what kind of database-tier parallelism Gartner is claiming is new in Oracle in 11g Release 2 — but I doubt it’s really new. Rather, what Oracle has done recently is make parallelism less administratively cumbersome.
• Vertica wasn’t really the first DBMS in the cloud. At most it was the first pure-play analytic DBMS to get there.