Cognos
Analysis of business intelligence pioneer Cognos. Also covered is Applix, vendor of the memory-centric MOLAP tool TM1, which was acquired by Cognos. Related subjects include:
- IBM, which has acquired Cognos
- Business intelligence
- Memory-centric data management
- MOLAP (Multidimensional OnLine Analytic Processing)
Cognos/State of Massachusetts scandal
I assumed this had been reported widely outside of Massachusetts, but a web search suggests otherwise.
The story is this: Cognos sold 20,000 seats of software to Massachusetts for $13 million. There were technical violations of purchase procedures, and other aspects of the deal that didn’t pass the smell test. After IBM bought Cognos, the deal was rescinded, and is being rebid. Read more
| Categories: Analytic technologies, Business intelligence, Cognos, Pricing | 2 Comments |
IBM acquires SolidDB to compete with Oracle TimesTen
IBM is acquiring Solid Information Technology, makers of solidDB. Some quick comments:
- solidDB is actually a very interesting hybrid disk/in-memory memory-centric database management system. However, the press release announcing the deal makes it sound as if solidDB is in-memory only.
- That strongly suggests that IBM is buying Solid mainly to compete with Oracle TimesTen. As of last June, solidDB was already IBM’s TimesTen answer via a partnership; this deal just solidifies that arrangement.
- This probably isn’t good news for Solid’s MySQL engine. That’s a pity, since solidDB technically has the potential to be the best MySQL engine around.
- Notwithstanding IBM’s presumed intentions, Solid’s main market success historically is as an embedded system in telecommunications equipment, network software, and similar systems.
- Last year I wrote a white paper on memory-centric data management, showcasing four products. IBM now has bought two of them, namely Solid’s and Applix’s (via Cognos).
- Comparisons to IBM’s embedded Java DBMS Cloudscape are pointless. That’s just a failed product vs. solidDB or Sybase SQL Anywhere, and IBM long ago cut its losses.
| Categories: Cache, Cognos, IBM and DB2, In-memory DBMS, Memory-centric data management, MySQL, OLTP, Oracle TimesTen, solidDB, Sybase | 4 Comments |
A quick survey of data warehouse management technology
There are at least 16 different vendors offering appliances and/or software that do database management primarily for analytic purposes.* That’s a lot to keep up with,. So I’ve thrown together a little overview of the analytic data management landscape, liberally salted with links to information about specific vendors, products, or technical issues. In some ways, this is a companion piece to my prior post about data warehouse appliance myths and realities.
*And that’s just the tabular/alphanumeric guys. Add in text search and you run the total a lot higher.
Numerous data warehouse specialists offer traditional row-based relational DBMS architectures, but optimize them for analytic workloads. These include Teradata, Netezza, DATAllegro, Greenplum, Dataupia, and SAS. All of those except SAS are wholly or primarily vendors of MPP/shared-nothing data warehouse appliances. EDIT: See the comment thread for a correction re Kognitio.
Numerous data warehouse specialists offer column-based relational DBMS architectures. These include Sybase (with the Sybase IQ product, originally from Expressway), Vertica, ParAccel, Infobright, Kognitio (formerly White Cross), and Sand. Read more
An interesting claim regarding BI openness
Analyst conference calls about merger announcements are generally pretty boring. Indeed, the companies involved tend to feel they are legally barred from saying anything interesting, by mandate of both the antitrust regulators and the SEC.
Still, such calls are joyful events, full of strategic happy talk. If one is really lucky, there may a virtuouso tap dancing exhibition as well. On today’s IBM/Cognos call, Cognos CEO Rob Ashe was asked whether he thought Cognos’ independence or lack thereof was as important today as he said it was after SAP announced its BOBJ takeover. Without missing a beat, he responded that there were two kinds of openness:
- Database openness (not important)
- ERP/business process openness (indeed important)
Hmm. I’m not so sure I agree. To begin with, there aren’t just two major points of potential integration. There’s also a whole lot of middleware: obviously data integration, but also app servers, portals, and query execution acceleration as well. Read more
| Categories: Analytic technologies, Business intelligence, Business Objects, Cognos, IBM and DB2, Memory-centric data management, ParAccel, SAP AG | 1 Comment |
IBM is buying Cognos – quick reactions
Some quick thoughts in connection with IBM’s just-announced plans to acquire Cognos.
1. Ironically, IBM just put out a press release describing a strong-sounding reseller partnership with Business Objects. The deal specified that
Business Objects will begin distributing and reselling IBM DB2 Warehouse with Business Objects XI and CFO Performance Management solutions. In addition, IBM will include a starter edition of Business Objects XI with DB2 and DB2 Warehouse.
Jeff Jones of IBM told me that they also had a partnership with Cognos, but with different details. I guess Cognos will eventually take over that deal, which is an obvious negative for Business Objects.
2. More generally, I can see where Cognos will now likely gain share at DB2 sites, and IBM/Ascential at Cognos sites. I can’t as easily see why Cognos would now lose share at Oracle or Teradata or Netezza sites, or why Ascential would lose share at SAP/BOBJ sites. So there seem to be some genuine synergies here, albeit perhaps modest ones.
3. Thus, I think the negatives in this deal for the remaining independents (Microstrategy, Information Builders, Informatica, etc.) will somewhat outweigh the positives.
4. I’m not a big fan of Cognos’ management, former CEO Ron Zambonini and a few other freethinkers excepted. So from that standpoint I don’t think they have a lot to lose being taken over by Big Blue.
5. Obviously, with most of the dominoes now fallen, the big question is about the future of BI as it – potentially – gets integrated into much larger enterprise technology suites. And I think the answer to that depends a lot more on technology than most people seem to realize. More on that subject later, but here’s one hint:
I think fixing the disappointment that is dashboards will involve taking query volumes up by at least 2 to 3 orders of magnitude. So as great as recent innovations in analytic query performance have been, I hope and trust that so far we’ve only seen the tip of the iceberg.
Links:
1. eWeek on the IBM/Business Objects deal.
2. Press release on the IBM/Business Objects deal.
3. Press release on the IBM/Cognos deal.
| Categories: Analytic technologies, Business intelligence, Business Objects, Cognos, IBM and DB2 | 5 Comments |
The era of memory-centric BI may have finally started
SAP is acquiring Business Objects. There’s nothing inherent in BI Accelerator’s design that ties it to NetWeaver, SAP star schema InfoCubes, or any other particular current implementation detail. So BI Accelerator could become a lot more than an afterthought.
Combine that with Cognos’s acquisition of Applix and the continued success of upstart QlikView, and we could finally see a general memory-centric BI boom.
Maybe. There have been a lot of false alarms before.
| Categories: Analytic technologies, Business intelligence, Business Objects, Cognos, Memory-centric data management, QlikTech and QlikView, SAP AG | 2 Comments |
Applix – Three huge opportunities Cognos will probably ignore
If I weren’t on a snorkeling vacation,* this might be a good time to write about why I once called Cognos “The Gang That Couldn’t Shoot Straight,” how Ron Zambonini used that label to help him gain the company’s top spot, why he’s such a big fan of mine, why I got my highest ever per-minute speaking fee to attend a Cognos sales kickoff event, why I went for a midnight touristing stroll in downtown Ottawa in zero degree Fahrenheit weather, or how I managed, while attending the aforementioned Cognos sales kickoff, to get snowed in for three days in, of all places, Dallas, Texas. But the wrasses and jacks await, so I’ll get straight to the point.
*Albeit fairly snorkel-free so far, thanks to Hurricane Felix. 
As I discussed at considerable length in a white paper, Applix’s core technology is fully-featured, memory-centric MOLAP. This is certainly cool technology, and I think it is actually unique. That it’s historically been positioned as the engine for a mid-range set of performance management tools is a travesty, a shame, the result of a prior merger – and also the quite understandable consequence of RAM limitations. However, RAM is ever cheaper and Applix’s technology is now 64-bit, so the RAM barriers have been relaxed. Cognos can take Applix’s TM1 engine high-end if it wants to. And boy, should Cognos ever want to. Indeed, there are three different great ways Cognos could package and position TM1:
- As a no-data-warehouse-design quick-start analytics engine analogous to QlikView (the fastest-growing and most important newish BI suite, open source perhaps excepted);
- As the most sophisticated and versatile planning tool this side of SAP’s APO (and while APO’s sophistication is not in dispute, its versatility is questionable anyway);
- As the processing hub for dashboards-done-right.
| Categories: Analytic technologies, Business intelligence, Cognos, Memory-centric data management, MOLAP | 6 Comments |
QlikView – a leader in memory-centric BI
QlikTech — the vendor of QlikView — contacted me to tell their memory-centric BI story. A Swedish company with >$23 million in estimated license revenue last year and a 100%ish growth rate, they claim to be the leader in that space, pulling ahead of Applix. But for now, I’ll call them “a” leader, and say that their story sounds like a hybrid between those of Applix (TM1 product) and SAP (BI Accelerator).
| Categories: Business intelligence, Cognos, Memory-centric data management, QlikTech and QlikView, SAP AG | 1 Comment |
Memory-centric data management whitepaper
I have finally finished and uploaded the long-awaited white paper on memory-centric data management.
This is the project for which I origially coined the term “memory-centric data management,” after realizing that the prevalent “in-memory DBMS” creates all sorts of confusion about how and whether data persists on disk. The white paper clarifies and updates points I have been making about memory-centric data management since last summer. Sponsors included:
- Applix, vendors of in-memory/memory-centric MOLAP tool TM1
- Progress Software, vendors of ObjectStore, an OODBMS that has more impressive references in-memory or otherwise memory-centric than it does in classical disk-based configurations, and also of the Apama stream processing products
- SAP, vendors of the BI Accelerator functionality of SAP NetWeaver, or whatever tortured name they want to give it this month — basically, that’s a very cool in-memory columnar data mart technology
- Solid Information Technology, vendor of hybrid in-memory/disk-based OLTP RDBMS. Historically focused on the embedded systems market, especially telecom and networking, they’ve recently been in the news because of a deal with MySQL that is designed to extend their reach.
- Intel, makers of the processors used to run a lot of the other sponsors’ products (including all BI Accelerator installations to date).
If there’s one area in my research I’m not 100% satisfied with, it may be the question of where the true hardware bottlenecks to memory-centric data management lie (it’s obvious that the bottleneck to disk-centric data management is random disk access). Is it processor interconnect (around 1 GB/sec)? Is it processor-to-cache connections (around 5 GB/sec)? My prior pronouncements, the main body of the white paper, and the Intel Q&A appendix to the white paper may actually have slightly different spins on these points.
And by the way — the current hard limit on RAM/board isn’t 2^64 bytes, but a “mere” 2^40. But don’t worry; it will be up to 2^48 long before anybody actually puts 256 gigabytes under the control of a single processor.
| Categories: Cognos, Companies and products, In-memory DBMS, Intel, Memory-centric data management, MOLAP, Open source, Progress, Apama, and DataDirect, SAP AG, solidDB | 2 Comments |
Defining and surveying “Memory-centric data management”
I’m writing more and more about memory-centric data management technology these days, including in my latest Computerworld column. You may be wondering what that term refers to. Well, I’ve basically renamed what are commonly called “in-memory DBMS,” for what I think is a very good reason: Most of the products in the category aren’t true DBMS, aren’t wholly in-memory, or both! Indeed, if you catch me in a grouchy mood I might argue that “in-memory DBMS” is actually a contradiction in terms.
I’ll give a quick summary of the vendors and products I am focusing on in this newly-named category, and it should be clearer what I mean:
- TimesTen (now owned by Oracle): TimesTen is the quintessentional “in-memory DBMS.” It’s a fairly full relational DBMS, but if you want to persist memory to disk it has to be handed off to a conventional DBMS. Historically, that has usually been MySQL or Oracle. TimesTen’s biggest market penetration has been in financial trading.
- Solid Information Technology‘s BoostEngine: Solid is a Finnish company (or was — it’s pretty American now) specializing in embedded DBMS sold mainly for telecommunication uses. Big OEM customers include several well-known telecom equipment manufacturers and HP (for OpenView). “Embedded” often means no DBA, no monitor, no keyboard — they box manufacturer installs it and there it stays for the life of the product. Solid has to offer strong replication capabilities, since its products are often used in highly distributed (e.g., multiblade, multibox) environments. So it’s taken the next step and exploited the replication by allowing customers to use some instances of the product disklessly.
- Event-stream products from Streambase and Progress: The canonical application for event-stream products is automating financial trading decisions based on the flow of market information. Mike Stonebraker, the brains behind Streambase, has recently popularized the idea; Progress bought Apama, who actually have been in the business longer. These applications require even more speed than the financial trading apps that TimesTen handles, and they discard most of the information they look at. In-memory is the only way to go.
- Progress’s ObjectStore: ObjectStore comes from the company Object Design, which merged into Excelon, which was acquired by Progress. It’s really a toolkit for building DBMS and similar systems, which is why it’s at various times been marketed as an OODBMS and an XML DBMS, without a lot of success either way. But there have been a few sterling apps built in ObjectStore even so, including a key part of the Amazon bookstore Despite this limited market success, a significant fraction of Progress’s best engineering talent has moved over to the Real-Time Division to focus on ObjectStore and other memory-centric products. The memory-centric aspect of ObjectStore is this: ObjectStore’s big virtue is that it gets objects from disk to memory and vice-versa very efficiently, then distributes and caches them around a network as needed. This was originally invented for client/server processing, but works fine in a multi-server thin client setup as well. And object processing, of course, relies on a whole lot of pointers. And pointer-chasing is pretty much the worst way to deal with the disk speed barrier, unless you do it in main memory.
- Applix‘s TM1: Like many companies in the analytics area, Applix has had trouble deciding whether it sells applications, BI system software, or both. But in any case its core technology is TM1, a memory-centric MOLAP offering. Traditional MOLAP products reside on the horns of a nasty dilemma: They rely on precalculation to give good performance, but that causes ghastly database explosion. Applix gets out of this problem by doing no precalculation whatsoever, loading the data into main memory, and executing all queries on the fly.
- SAP’s BI Accelerator: SAP is building out an elaborate technology stack with NetWeaver, especially in the BI area. One important aspect is that the full data warehouse is logically broken (or copied) into a series of data marts called “InfoCubes.” BI Accelerator takes the logical next step, loading an entire InfoCube into main memory. Almost every query is executed via a full table scan, which would be insane on disk but makes perfect sense when the data is already in RAM.
So there you have it. There are a whole lot of technologies out there that manage data in RAM, in ways that would make little or no sense if disks were more intimately involved. Conventional DBMS also try to exploit RAM and limit disk access, via caching; but generally the data access methods they use in RAM are pretty similar to those they use when going out to disk. So memory-centric systems can have a major advantage.