High-performance analytics
For the past few months, I’ve collected a lot of data points to the effect that high-performance analytics – i.e., beyond straightforward query — is becoming increasingly important. And I’ve written about some of them at length. For example:
- MapReduce – controversial or in some cases even disappointing though it may be – has a lot of use cases.
- It’s early days, but Netezza and Teradata (and others) are beefing up their geospatial analytic capabilities.
- Memory-centric analytics is in the spotlight.
Ack. I can’t decide whether “analytics” should be a singular or plural noun. Thoughts?
Another area that’s come up which I haven‘t blogged about so much is data mining in the database. Data mining accounts for a large part of data warehouse use. The traditional way to do data mining is to extract data from the database and dump it into SAS. But there are problems with this scenario, including: Read more
| Categories: Aster Data, Data warehousing, EAI, EII, ETL, ELT, ETLT, Greenplum, MapReduce, Netezza, Oracle, Parallelization, SAS Institute, Teradata | 6 Comments |
Introduction to Talend
I didn’t spend much time on the show floor at Teradata Partners, but I did connect with Yves de Montcheuil of Talend for a couple of little chats. Highlights of the Talend story include: Read more
Multitenancy hype is getting out of control
I posted recently on SaaS-data-integration-in-the-cloud, and a couple of vendors stopped by the comment thread to shared what they do. One was Boomi, which has a blog that does a good job of spelling out its opinions. What the Boomi blog is not so good at, however, is giving any good reasons why one should share those opinions.
I refer specifically to a couple of posts claiming that multitenancy is somehow crucial for SaaS data integration to work. To this I can only say — huh? A decent data integration system should be able to handle many parallel threads at once, connecting many pairs of databases at once. So the hard part of multitenancy is pretty much “free.” If, even so, the integration provider chooses not to go fully multitenant, whose business is it but theirs? Read more
| Categories: Data integration and middleware, EAI, EII, ETL, ELT, ETLT, Software as a Service (SaaS) | 7 Comments |
Everybody’s putting integration services in the cloud
Both Pervasive Software and Cast Iron Systems told me recently of fairly pure cloud offerings. In this, they’re joining Informatica, which started offering Salesforce.com integration-as-a-service back in 2006. So far as I can tell, the three vendors are doing somewhat different things. Read more
| Categories: Cast Iron Systems, Cloud computing, Data integration and middleware, EAI, EII, ETL, ELT, ETLT, Informatica, Pervasive Software, Software as a Service (SaaS) | 8 Comments |
Schema flexibility and XML data management
Conor O’Mahony, marketing manager for IBM’s DB2 pureXML, talks a lot about one of my favorite hobbyhorses — schema flexibility — as a reason to use an XML data model. In a number of industries he sees use cases based around ongoing change in the information being managed:
- Tax authorities change their rules and forms every year, but don’t want to do total rewrites of their electronic submission and processing software.
- The financial services industry keeps inventing new products, which don’t just have different terms and conditions, but may also have different kinds of terms and conditions.
- The same, to some extent, goes for the travel industry, which also keeps adding different kinds of offers and destinations.
- The energy industry keeps adding new kinds of highly complex equipment it has to manage.
Conor also thinks market evidence shows that XML’s schema flexibility is important for data interchange. Read more
| Categories: Data models and architecture, EAI, EII, ETL, ELT, ETLT, IBM and DB2, pureXML, Structured documents | 3 Comments |
Vertical market XML standards
Tracking the alphabet soup of vertical market XML standards is hard. So as a starting point, I’m splitting a list I got from IBM into a standalone post.
Among the most important or successful IBM pureXML–supported standards, in terms of downloads and other evidence of customer interest, are: Read more
| Categories: Application areas, EAI, EII, ETL, ELT, ETLT, IBM and DB2, pureXML, Structured documents | 2 Comments |
Overview of IBM DB2 pureXML
On August 29, I had a great call with IBM about DB2 pureXML (most of the IBM side of the talking was done by Conor O’Mahony and Qi Jin). I’m finally getting around to writing it up now. (The world of tabular data warehousing has kept me just a wee bit busy …)
As I write it, I see there are a considerable number of holes, but that’s the way it seems to go when researching XML storage. I’m also writing up a September call from which I finally figured out (I think) the essence of how MarkLogic Server works – but only after five months of trying. It turns out that MarkLogic works rather differently from DB2 pureXML. Not coincidentally, IBM and Mark Logic focus on rather different use cases for native XML storage.
What I understand so far about the basic DB2 pureXML architecture goes like this: Read more
| Categories: EAI, EII, ETL, ELT, ETLT, IBM and DB2, pureXML, Structured documents | 7 Comments |
Three approaches to parallelizing data transformation
Many MPP data warehousing vendors have told me their products are used for ELT (Extract/Load/Transform) instead of ETL (Extract/Transform/Load). I.e., needed data transformations are done on the MPP system, rather than on the — probably SMP — system the data comes from.* If the data transformation is being applied on a record-by-record basis, then it’s automatically fully parallelized. Even if the transforms are more complex, considerable parallel processing may still be going on.
*Or it’s some of each, at which point it’s called ETLT — I bet you can work out what that stands for.
| Categories: Aster Data, Data integration and middleware, Data warehousing, EAI, EII, ETL, ELT, ETLT, MapReduce, Parallelization, Pervasive Software | 8 Comments |
Google has thousands of internal data formats, mostly simple ones
In connection with the release of Protocol Buffers, Kenton Varda of Google wrote: Read more
| Categories: Data integration and middleware, Google | 2 Comments |
Pervasive is also pursuing simplicity and SaaS integration
I blogged recently about Cast Iron Systems, a simplicity-oriented data integration appliance vendor that is increasingly focusing on the SaaS market. Well, Pervasive Software is doing something similar.
Via Data Integrator, Pervasive is a leader in the low-cost integration market, with revenue split about 50/25/25 between direct sales, ISVs, and SaaS. Pervasive fondly believes that its products cost half as much as Cast Iron’s, and wind up taking no more installation effort when you factor in Pervasive’s broader capabilities in areas such as workflow. However, there’s some doubt as to whether this is apples-to-apples. Cast Iron does include hardware, after all, and as Pervasive itself points out, Cast Iron will bundle some professional services into a sale if you ask nicely.
Two things are new. Read more