GIS and geospatial
Analysis of data management technology optimized for geospatial data, whether by specialized indexing or user-defined functions
Various quick notes
As you might imagine, there are a lot of blog posts I’d like to write I never seem to get around to, or things I’d like to comment on that I don’t want to bother ever writing a full post about. In some cases I just tweet a comment or link and leave it at that.
And it’s not going to get any better. Next week = the oft-postponed elder care trip. Then I’m back for a short week. Then I’m off on my quarterly visit to the SF area. Soon thereafter I’ve have a lot to do in connection with Enzee Universe. And at that point another month will have gone by.
Anyhow: Read more
| Categories: Analytic technologies, Business intelligence, Data warehousing, Exadata, GIS and geospatial, Google, IBM and DB2, Netezza, Oracle, Parallelization, SAP AG, SAS Institute | 3 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 | 3 Comments |
This week at the Teradata Partners user conference
Teradata tells me that its press embargoes are ending at 9:00 this morning. Here are some highlights of what’s going on, although names, dates, and details will have to await conversations and press releases this week.
- Teradata is productizing “private cloud,” under names including “Teradata Enterprise Analytics Cloud,” “Teradata Agile Analytics Cloud,” and “Teradata Elastic Mart Builder.” I.e., Teradata hopes to leapfrog Greenplum in its “Enterprise Data Cloud” strategy. This is only fair, in that Greenplum lifted the idea from Teradata and eBay in the first place. It also provides major support for what I think is an extremely sensible trend. Give or take issues of who announces and ships what a couple months before or after a competitor, my early thinking is that the main differences between Greenplum and Teradata in this regard will be:
- Virtual as opposed to just physical data marts, based on robust workload management software. (Advantage: Teradata)
- Pricing, deployment options. (Advantage: Greenplum)
- Features that don’t directly relate to enterprise/private cloud. (Advantage: Either, often Teradata.)
- Teradata is generally strengthening its data movement technology, e.g. for making various appliances work in sync. I’m not too clear yet on the details of that. I think this is what Teradata’s phrase “ecosystem management” refers to.
- Teradata is (pre-)announcing – at least as a statement of direction — an appliance based on solid-state drives (SSDs). I’ve thought for a while that Teradata was a leader in thinking through the issues around solid-state memory in data warehousing, so it makes sense that they’re among the leaders in actually coming to market as well. I plan to say more after meeting with, e.g., Carson Schmidt.
- Teradata has achieved a 300%ish speed-up in geospatial processing. I gather this is largely a byproduct of the parallel analytics work Teradata did around strengthening its SAS integration. However, there don’t seem to be a lot of Teradata geospatial users yet.
- Teradata Express, Teradata’s free Windows-based crippleware, is being ported to Amazon EC2 and VMware as well. Presumably to avoid cannibalizing Teradata product sales, there are quite a few limitations on Teradata Express, including system capacity, database size, and “no production use.”
- Teradata continues to extend its optimizations to handle queries issued by business intelligence tools. Previously, the focus of what Teradata discussed in this regard was query rewrite. But soon automatic recommendation and creation of Aggregate Join Indexes – i.e.., materialized views – will be included as well.
Issues in scientific data management
In the opinion of the leaders of the XLDB and SciDB efforts, key requirements for scientific data management include:
- A data model based on multidimensional arrays, not sets of tuples
- A storage model based on versions and not update in place
- Built-in support for provenance (lineage), workflows, and uncertainty
- Scalability to 100s of petabytes and 1,000s of nodes with high degrees of tolerance to failures
- Support for “external” data objects so that data sets can be queried and manipulated without ever having to be loaded into the database
- Open source in order to foster a community of contributors and to insure that data is never “locked up” — a critical requirement for scientists
However: Read more
Teradata 13 focuses on advanced analytic performance
Last October I wrote about the Teradata 13 release of Teradata’s database management software. Teradata 13, which will be used across the various Teradata product lines, has now been announced for GCA (General Customer Availability)*. So far as I can tell, there were two main points of emphasis for Teradata 13:
- Performance (of course, performance is a point of emphasis for almost any release of any analytic DBMS product), especially but not only in the areas of aggregates, ETL (Extract/Transform/Load), and UDFs.
- UDFs (User Defined Functions), especially but not only in the areas of data mining and geospatial analysis.
To put it even more concisely, the focus of Teradata 13 is on advanced analytic performance, although there of course are some enhancements in simple query performance and in analytic functionality as well. Read more
Teradata Developer Exchange (DevX) begins to emerge
Every vendor needs developer-facing web resources, and Teradata turns out to have been working on a new umbrella site for its. It’s called Teradata Developer Exchange — DevX for short. Teradata DevX seems to be in a low-volume beta now, with a press release/bigger roll-out coming next week or so. Major elements are about what one would expect:
- Articles
- Blogs
- Downloads
- Surprisingly, so far as I can tell, no forums
If you’re a Teradata user, you absolutely should check out Teradata DevX. If you just research Teradata — my situation 
— there are some aspects that might be of interest anyway. In particular, I found Teradata’s downloads instructive, most particularly those in the area of extensibility. Mainly, these are UDFs (User-Defined Functions), in areas such as:
- Compression
- Geospatial data
- Imitating Oracle or DB2 UDFs (as migration aids)
Also of potential interest is a custom-portlet framework for Teradata’s management tool Viewpoint. A straightforward use would be to plunk some Viewpoint data into a more general system management dashboard. A yet cooler use — and I couldn’t get a clear sense of whether anybody’s ever done this yet — would be to offer end users some insight as to how long their queries are apt to run.
| Categories: Database compression, Emulation, transparency, portability, GIS and geospatial, Teradata | 2 Comments |
IBM’s Oracle emulation strategy reconsidered
I’ve now had a chance to talk with IBM about its recently-announced Oracle emulation strategy for DB2. (This is for DB2 9.7, which I gather has been quasi-announced in April, will be re-announced in May, and will be re-re-announced as being in general availability in June.)
Key points include:
- This really is more like Oracle emulation than it is transparency, a term I carelessly used before.
- IBM’s Oracle emulation effort is focused on two technological goals:
- Making it easy for an Oracle application to be ported to DB2.
- Making it easy for an Oracle developer to develop for DB2.
- The initial target market for DB2’s Oracle emulation is ISVs (Independent Software Vendors) much more than it is enterprises. IBM suggested there were a couple hundred early adopters, and those are primarily in the ISV area.
Because of Oracle’s market share, many ISVs focus on Oracle as the underlying database management system for their applications, whether or not they actually resell it along with their own software. IBM proposed three reasons why such ISVs might want to support DB2: Read more
| Categories: Data types, Emulation, transparency, portability, EnterpriseDB and Postgres Plus, GIS and geospatial, IBM and DB2, Market share, Oracle, Pricing, Structured documents, Text | 10 Comments |
More Oracle notes
When I went to Oracle in October, the main purpose of the visit was to discuss Exadata. And so my initial post based on the visit was focused accordingly. But there were a number of other interesting points I’ve never gotten around to writing up. Let me now remedy that, at least in part. Read more
| Categories: Complex event processing (CEP), Data types, Data warehousing, Database compression, GIS and geospatial, MOLAP, Oracle, SAP AG, Theory and architecture, Web analytics | 9 Comments |
Teradata Geospatial, and datatype extensibility in general
As part of it’s 13.0 release this week, Teradata is productizing its geospatial datatype, which previously was just a downloadable library. (Edit: More precisely, Teradata announced 13.0, which will actually be shipped some time in 2009.) What Teradata Geospatial now amounts to is:
- User-defined functions (UDF) written by Teradata (this is the part that existed before).
- (Possibly new) Enhanced implementations of the Teradata geospatial UDFs, for better performance.
- (Definitely new) Optimizer awareness of the Teradata geospatial UDFs.
Teradata also intends in the future to implement actual geospatial indexing; candidates include r-trees and tesselation.
Hearing this was a good wake-up call for me, because in the past I’ve conflated two issues on datatype extensibility, namely:
- Whether the query executer uses a special access method (i.e., index type) for the datatype
- Whether the optimizer is aware of the datatypes.
But as Teradata just pointed out, those two issues can indeed be separated from each other.
| Categories: Data types, Data warehousing, GIS and geospatial, Teradata | 1 Comment |
Netezza and Teradata on analytic geospatial data management
Geospatial data management is one of the flavors of the month:
- Last week, Teradata claimed it has the most sophisticated analytic geospatial data management capability.
- Also last week, Netezza’s newly acquired Netezza Spatial technology attracted a lot of attention.
- This week, Oracle called attention to its geospatial capabilities.
So I asked Netezza and Teradata what this geospatial analytics stuff is all about. Read more
| Categories: Analytic technologies, Data warehousing, GIS and geospatial, Netezza, Teradata | 3 Comments |