Cloud computing
Analysis of cloud computing, especially as applied to database management and analytics. Related subjects include:
Open issues in database and analytic technology
The last part of my New England Database Summit talk was on open issues in database and analytic technology. This was closely intertwined with the previous section, and also relied on a lot that I’ve posted here. So I’ll just put up a few notes on that part, with lots of linkage to prior discussion of the same points. Read more
Introduction to Gooddata
Around the end of the Cold War, Esther Dyson took it upon herself to go repeatedly to Eastern Europe and do a lot of rah-rah and catalysis, hoping to spark software and other computer entrepreneurs. I don’t know how many people’s lives she significantly affected – I’d guess it’s actually quite a few – but in any case the number is not zero. Roman Stanek, who has built and sold a couple of software business, cites her as a key influence setting him on his path.
Roman’s latest venture is business intelligence firm Gooddata. Gooddata was founded in 2007 and has been soliciting and getting attention for a while, so I was surprised to learn that Gooddata officially launched just a few weeks ago. Anyhow, some less technical highlights of the Gooddata story include: Read more
Boston Big Data Summit keynote outline
Last month, Bob Zurek asked me to give a talk on “Big Data”, where “big” is anything from a few terabytes on up, then moderate a panel on cloud computing. We agreed that I could talk just from notes, without slides. So, since I have them typed up, I’m posting them below.
Aster Data 4.0 and the evolution of “advanced analytic(s) servers”
Since Linda and I are leaving on vacation in a few hours, Aster Data graciously gave me permission to morph its “12:01 am Monday, November 2” embargo into “late Friday night.”
Aster Data is officially announcing the 4.0 release of nCluster. There are two big pieces to this announcement:
- Aster is offering a slick vision for integrating big-database management and general analytic processing on the same MPP cluster, under the not-so-slick name “Data-Application Server.”
- Aster is also offering a sophisticated vision for workload management.
In addition, Aster has matured nCluster in various ways, for example cleaning up a performance problem with single-row updates.
Highlights of the Aster “Data-Application Server” story include: Read more
| Categories: Aster Data, Cloud computing, Data warehousing, EAI, EII, ETL, ELT, ETLT, MapReduce, Market share and customer counts, Teradata, Theory and architecture, Workload management | 9 Comments |
Teradata’s nebulous cloud strategy
As the pun goes, Teradata’s cloud strategy is – well, it’s somewhat nebulous. More precisely, for the foreseeable future, Teradata’s cloud strategy is a collection of rather disjointed parts, including:
- What Teradata calls the Teradata Agile Analytics Cloud, which is a combination of previously existing technology plus one new portlet called the Teradata Elastic Mart(s) Builder. (Teradata’s Elastic Mart(s) Builder Viewpoint portlet is available for download from Teradata’s Developer Exchange.)
- Teradata Data Mover 2.0, coming “Soon”, which will ease copying (ETL without any significant “T”) from one Teradata system to another.
- Teradata Express DBMS crippleware (1 terabyte only, no production use), now available on Amazon EC2 and VMware. (I don’t see where this has much connection to the rest of Teradata’s cloud strategy, except insofar as it serves to fill out a slide.)
- Unannounced (and so far as I can tell largely undesigned) future products.
Teradata openly admits that its direction is heavily influenced by Oliver Ratzesberger at eBay. Like Teradata, Oliver and eBay favor virtual data marts over physical ones. That is, Oliver and eBay believe that the ideal scenario is that every piece of data is only stored once, in an integrated Teradata warehouse. But eBay believes and Teradata increasingly agrees that users need a great deal of control over their use of this data, including the ability to import additional data into private sandboxes, and join it to the warehouse data already there. Read more
| Categories: Analytic technologies, Cloud computing, Data integration and middleware, Data warehousing, EAI, EII, ETL, ELT, ETLT, eBay, Teradata, Theory and architecture | 5 Comments |
I have some presentations coming up (all on October Thursdays)
On Thursday, October 15, and two different times (10:00 am and 1:00 pm Eastern time), I’ll be giving a webinar for Aster Data on MapReduce. The content is very much work in progress, but it definitely will:
- Be overviewy in nature
- Emphasize SQL/MapReduce integration
Then, on the evening of Thursday, October 22, there’s something called the Boston Big Data Summit, in Waltham, where “Big Data” evidently is to be construed as anything from a few terabytes on up. (Things are smaller in the Northeast than in California …) It’s being put together by Amrith Kumar (who I don’t really know) and Bob Zurek (who everybody knows). This is the inaguaral meeting. It seems I’m both giving the keynote and running the subsequent panel, one of whose participants will be Ellen Rubin. Read more
| Categories: Analytic technologies, Aster Data, Cloud computing, MapReduce, Presentations | 4 Comments |
Sneakernet to the cloud
Recently, Amazon CTO Werner Vogels put up a blog post which suggested that, now and in the future, the best way to get large databases into the cloud is via sneakernet. In some circumstances, he is surely right. Possible implications include:
- When sending data to the cloud, you probably want to compress it to the max before sending. Clearpace’s new RainStor structured-data archiving service emphasizes that idea. RainStor marketing says cloud, cloud, cloud — but Clearpace thinks you really should have a bit of its software onsite too, to compress the data before sending it across the wire.
- Getting data from one cloud to another cloud could be problematic. I’m fond of saying that weblog data naturally lives in the cloud at your hosting company’s location, so you should analyze it there too. But this makes the most sense if you analyze it or at least filter/reduce it in place. (That said, the really, really big web companies have lots of different data centers, and presumably do move huge amounts of log data from place to place.)
But for one-time moves of data sets — sure, sneaker net/snail mail should work just fine.
| Categories: Amazon and its cloud, Cloud computing, Database compression, EAI, EII, ETL, ELT, ETLT, Web analytics | 2 Comments |
Amazon Elastic MapReduce
Amazon is introducing a beta of Amazon Elastic MapReduce. What it boils down to is cheap, on-demand Hadoop.
This seems like a great way to experiment with MapReduce and see if you like it. But for serious use, I don’t know why you wouldn’t prefer MapReduce more closely integrated into a DBMS.
| Categories: Amazon and its cloud, Cloud computing, MapReduce | 1 Comment |
April Fool’s Day highlights
Amazon says it’s taking “cloud” computing to new heights, as it were.
Derivative funds and large government-subsidized entities will be especially interested in FACE’s transmodal operation. They can allocate a dedicated FACE, load it up with data, and then send it out to sea to perform advanced processing in safety. The government will have absolutely no chance of acting against them, because they will be too busy trying to decide which Federal Air Regulation (FAR) was violated, not to mention scheduling news conferences.
First excellent April Fool’s joke I saw this year was from The Guardian. The best so far is from Expedia. Others are linked in my Twitter feed. And personally, I’m encouraging the concept of April No-Fooling Day.
| Categories: Amazon and its cloud, Cloud computing, Humor | 1 Comment |
IBM in the cloud
IBM is making DB2, Informix Dynamic Server, and other products available in the Amazon cloud. The press release says test and development are free, while production will be charged at an hourly rate. No doubt more price details will be forthcoming when the whole thing is fully in production.
Frankly, I’ve lost track of who all has some kind of cloud or SaaS offering now. The list is at least Oracle, IBM, presumably Microsoft, MySQL (via Elastra, and also at almost every web host), PostgreSQL (ditto, more or less), EnterpriseDB, Kognitio, Vertica, Netezza, Aster Data. No doubt I’m forgetting a bunch more.
| Categories: Cloud computing, Data warehousing, IBM and DB2, Pricing | 2 Comments |