Microsoft and SQL*Server
Microsoft’s efforts in the database management, analytics, and data connectivity markets. Related subjects include:
- DATAllegro, which is being bought by Microsoft
- (in Text Technologies) Microsoft in the search, online media, and social software markets
- (in The Monash Report) Strategic issues for Microsoft, and Microsoft Office
- (in Software Memories) Historical notes on Microsoft
The Netezza and IBM DB2 approaches to compression
Thursday, I spent 3 ½ hours talking with 10 of Netezza’s more senior engineers. Friday, I talked for 1 ½ hours with IBM Fellow and DB2 Chief Architect Tim Vincent, and we agreed we needed at least 2 hours more. In both cases, the compression part of the discussion seems like a good candidate to split out into a separate post. So here goes.
When you sell a row-based DBMS, as Netezza and IBM do, there are a couple of approaches you can take to compression. First, you can compress the blocks of rows that your DBMS naturally stores. Second, you can compress the data in a column-aware way. Both Netezza and IBM have chosen completely column-oriented compression, with no block-based techniques entering the picture to my knowledge. But that’s about as far as the similarity between Netezza and IBM compression goes. Read more
| Categories: Data warehousing, Database compression, IBM and DB2, Microsoft and SQL*Server, Netezza | 9 Comments |
Notes on SciDB and scientific data management
I firmly believe that, as a community, we should look for ways to support scientific data management and related analytics. That’s why, for example, I went to XLDB3 in Lyon, France at my own expense. Eight months ago, I wrote about issues in scientific data management. Here’s some of what has transpired since then.
The main new activity I know of has been in the open source SciDB project. Read more
| Categories: Analytic technologies, Data warehousing, GIS and geospatial, Microsoft and SQL*Server, SciDB, Scientific research, Web analytics, eBay | 2 Comments |
Intelligent Enterprise’s Editors’/Editor’s Choice list for 2010
As he has before, Intelligent Enterprise Editor Doug Henschen
- Personally selected annual lists of 12 “Most influential” companies and 36 “Companies to watch” in analytics- and database-related sectors.
- Made it clear that these are his personal selections.
- Nonetheless has called it an Editors’ Choice list, rather than Editor’s Choice.
(Actually, he’s really called it an “award.”)
Facts and rumors
- Vertica is putting out a press release today touting its 100th customer, and talking of triple digit growth last year.
- Multiple sources have told me that the DATAllegro system is being thrown out of Dell, so evidently Dell is telling this to one and all. If that goes through, this would presumably leave TEOCO as DATAllegro’s single happy customer. (I haven’t checked with Microsoft for its view.)
- A rumor has it that Infiniband technology vendor Voltaire, Ltd. privately claims triple-digit sales of switches for Exadata 1 (I think that one would be one switch per Exadata installation, not per rack). Based just on a quick glance, this is far from confirmed by Voltaire’s earnings conference call transcripts or SEC filings. However, the most recent transcript does seem to indicate Voltaire got multiple Exadata deals in the telecommunications sector, and suggests some Exadata penetration in other sectors as well.
- I was told of a classified-agency user that has >1 petabyte of data on Exadata 1 and 600 terabytes or so on Netezza. My not-obviously-biased source says the agency is distinctly happier with Netezza than Exadata.
- Like ParAccel, Oracle just got dinged for TPC-related misbehavior.
- Rumor has it that Sun has no intention of helping ParAccel rerun its withdrawn TPC-H benchmark.
- ParAccel has withdrawn the claim from its home page to be the “CERTIFIED” price-performance leader. This seems to confirm that the claim was a reference to the TPC-H. In my opinion, that was a gross misrepresentation of what the TPC-H shows.
Xkoto Gridscale highlights
I talked yesterday with cofounders Albert Lee and Ariff Kassam of Xkoto. Highlights included: Read more
| Categories: Clustering, IBM and DB2, Market share, Microsoft and SQL*Server, Parallelization, Pricing, Xkoto | 14 Comments |
Not-so-great moments in planning
| Categories: Analytic technologies, Fun stuff, Humor, Microsoft and SQL*Server | Leave a Comment |
Update on Microsoft’s Madison and Fast Track data warehouse products
I chatted with Stuart Frost of Microsoft yesterday. Stuart is and remains GM of Microsoft’s data warehouse product unit, covering about $1 billion or so of revenue. While rumors of Stuart’s departure from Microsoft are clearly exaggerated, it does seem that his role is more one of coordination than actual management.
Microsoft Madison availability remains scheduled for H1 2010. Nothing new there. Tangible progress includes a few customer commitments of various sorts, including one outright planned purchase (due to some internal customer considerations around using up a budget). At the moment various Microsoft Madison technology “previews” are going on, which seem to amount to proofs-of-concept, that:
- Start with actual customer data (some from Microsoft, some from outside)
- Generate larger synthesized data sets based on those (database size seems to be 10-100 TB)
- Run in Microsoft data centers or “technology centers”, rather than on customer premises.
The basic Microsoft Madison product distribution strategy seems to be: Read more
My current customer list among the analytic DBMS specialists
(This is an updated version of an August, 2008 post.)
One of my favorite pages on the Monash Research website is the list of many current and a few notable past customers. (Another favorite page is the one for testimonials.) For a variety of reasons, I won’t undertake to be more precise about my current customer list than that. But I don’t think it would hurt anything to list the analytic/data warehouse DBMS/appliance specialists in the group. They are:
- Aster Data
- Greenplum
- Infobright
- Kickfire
- Kognitio
- Microsoft
- Netezza (my biggest client this year, probably, because of all the Enzee Universe appearances)
- Sybase
- Teradata
- Vertica
- Attivio, which may or may not be construed as being in the analytic DBMS business
- Clearpace, ditto
All of those are Monash Advantage members.
If you care about all this, you may also be interested in the rest of my standards and disclosures.
| Categories: About this blog, Aster Data, Data warehousing, Greenplum, Infobright, Kickfire, Microsoft and SQL*Server, Netezza, Sybase, Teradata, Vertica Systems | 4 Comments |
The future of data marts
Greenplum is announcing today a long-term vision, under the name Enterprise Data Cloud (EDC). Key observations around the concept — mixing mine and Greenplum’s together — include:
- Data marts aren’t just for performance (or price/performance). They also exist to give individual analysts or small teams control of their analytic destiny.
- Thus, it would be really cool if business users could have their own analytic “sandboxes” — virtual or physical analytic databases that they can manipulate without breaking anything else.
- In any case, business users want to analyze data when they want to analyze it. It is often unwise to ask business users to postpone analysis until after an enterprise data model can be extended to fully incorporate the new data they want to look at.
- Whether or not you agree with that, it’s an empirical fact that enterprises have many legacy data marts (or even, especially due to M&A, multiple legacy data warehouses). Similarly, it’s an empirical fact that many business users have the clout to order up new data marts as well.
- Consolidating data marts onto one common technological platform has important benefits.
In essence, Greenplum is pitching the story:
- Thesis: Enterprise Data Warehouses (EDWs)
- Antithesis: Data Warehouse Appliances
- Synthesis: Greenplum’s Enterprise Data Cloud vision
When put that starkly, it’s overstated, not least because
Specialized Analytic DBMS != Data Warehouse Appliance
But basically it makes sense, for two main reasons:
- Analysis is performed on all sorts of novel data, from sources far beyond an enterprise’s core transactions. This data neither has to fit nor particularly benefits from being tightly fitted into the core enterprise data model. Requiring it to do so is just an unnecessary and painful bureaucratic delay.
- On the other hand, consolidation can be a good idea even when systems don’t particularly interoperate. Data marts, which commonly do in part interoperate with central data stores, have all the more reason to be consolidated onto a central technology platform/stack.
Reinventing business intelligence
I’ve felt for quite a while that business intelligence tools are due for a revolution. But I’ve found the subject daunting to write about because — well, because it’s so multifaceted and big. So to break that logjam, here are some thoughts on the reinvention of business intelligence technology, with no pretense of being in any way comprehensive.
Natural language and classic science fiction
Actually, there’s a pretty well-known example of BI near-perfection — the Star Trek computers, usually voiced by the late Majel Barrett Roddenberry. They didn’t have a big role in the recent movie, which was so fast-paced nobody had time to analyze very much, but were a big part of the Star Trek universe overall. Star Trek’s computers integrated analytics, operations, and authentication, all with a great natural language/voice interface and visual displays. That example is at the heart of a 1998 article on natural language recognition I just re-posted.
As for reality: For decades, dating back at least to Artificial Intelligence Corporation’s Intellect, there have been offerings that provided “natural language” command, control, and query against otherwise fairly ordinary analytic tools. Such efforts have generally fizzled, for reasons outlined at the link above. Wolfram Alpha is the latest try; fortunately for its prospects, natural language is really only a small part of the Wolfram Alpha story.
A second theme has more recently emerged — using text indexing to get at data more flexibly than a relational schema would normally allow, either by searching on data values themselves (stressed by Attivio) or more by searching on the definitions of pre-built reports (the Google OneBox story). SAP’s Explorer is the latest such view, but I find Doug Henschen’s skepticism about SAP Explorer more persuasive than Cindi Howson’s cautiously favorable view. Partly that’s because I know SAP (and Business Objects); partly it’s because of difficulties such as those I already noted.
Flexibility and data exploration
It’s a truism that each generation of dashboard-like technology fails because it’s too inflexible. Users are shown the information that will provide them with the most insight. They appreciate it at first. But eventually it’s old hat, and when they want to do something new, the baked-in data model doesn’t support it.
The latest attempts to overcome this problem lie in two overlapping trends — cool data exploration/visualization tools, and in-memory analytics. Read more