Software as a Service (SaaS)

Analysis of software-as-a-service offerings with a database or analytic focus, or data connectivity tools focused on SaaS. Related subjects include:

February 1, 2010

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

December 30, 2009

More miscellany

Adding to yesterday’s varied quick comments: Read more

December 27, 2009

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

November 23, 2009

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.

Read more

October 30, 2009

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:

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

October 27, 2009

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:

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

October 9, 2009

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:

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

July 7, 2009

Hasso Plattner calls for in-memory OLTP column stores

Former SAP CEO Hasso Plattner has written a paper called A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database, in association with a SIGMOD keynote address.* The approach Plattner advocates is an MPP in-memory column store, presumably somewhat akin to SAP’s frequently renamed Business Warehouse Accelerator/Business Intelligence Accelerator/BWA/BIA/Son-of-TREX technology. There also are strong similarities to the MPP in-memory row store project H-Store/VoltDB, although I don’t know whether Plattner would go so far as to adopt the H-Store view that all transactions should run in stored procedures. Unsurprisingly, SAP applications are used as the OLTP paradigm throughout.

*Thanks to Dave Kellogg for tipping me off to Plattner’s paper. I only went to two SIGMOD sessions, neither of which was Plattner’s. Nobody actually mentioned Plattner’s talk to me when I was down at SIGMOD.

Perhaps the most interesting part is Plattner’s claim that what’s demanding about OLTP isn’t database updating per se, but rather maintaining aggregates for quick-response analytics. In his main example of that point, Plattner proposes a real-life “more than 18″ table schema, of which 2 are base tables, and (most of?) the rest are materialized views that his proposed database architecture dispenses with (because analytic performance is sufficiently good without them). Thus, Plattner’s core columnar argument seemingly is

columnar –> natively fast analytics –> no need to maintain aggregates –> much lower update burden.

That said — if Plattner’s paper contained a clear statement of how much more expensive it is to insert or update a single row in a columnar vs. row-based system, I overlooked it. Instead, Plattner seems to be arguing that the volume of base-table updates is low enough that — whatever it may be — column-store update overhead is an acceptable price to pay.  (At one point he claims that only 5% of the data inserted in a financial application ever gets changed.) That may actually be true in a financial accounting system, but seems more questionable in a sufficiently large application that gets its updates from automatic devices, or from the consumer web.

Other highlights include: Read more

May 29, 2009

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:

But for one-time moves of data sets — sure, sneaker net/snail mail should work just fine.

April 3, 2009

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.

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