Data types
Analysis of data management technology optimized for specific datatypes, such as text, geospatial, object, RDF, or XML. Related subjects include:
- Any subcategory
- Database diversity
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 |
Oracle spotlights its datatype support
Oracle put out a flurry of press releases today in conjunction with Oracle OpenWorld. One, which was simply positioned as a report on some “mission-critical” customer apps, caught my eye because all four detailed examples involved nonstandard datatypes:
- Two Oracle Spatial
- One “semantic,” which in Oracle lingo seems to mean — you guessed it — RDF
- One DICOM, which seems to be a medical imaging datatype.
| Categories: Data types, GIS and geospatial, Oracle, RDF and graphs | 3 Comments |
Peter Batty on Netezza Spatial
As previously noted, I’m not up to speed on Netezza Spatial. Phil Francisco of Netezza has promised we’ll fix that ASAP. In the mean time, I found a blog by a guy named Peter Batty, who evidently:
- Knows a lot about geospatial data and its uses
- Is consulting to Netezza
- Is smart
Batty offers a lot of detail in two recent posts, intermixed with some gollygeewhiz about Netezza in general. If you’re interested in this stuff, Batty’s blog is well worth checking out. Read more
| Categories: Analytic technologies, Data warehousing, GIS and geospatial, Netezza, Telecommunications | 2 Comments |
Teradata decides to compete head-on as a data warehouse appliance vendor
In a press release today that is surely timed to impinge on the Netezza user conference news cycle, Teradata has come out swinging. Highlights include:
- Teradata, which long avoided the “appliance” term, now says it sells both “data warehouse appliances” and “data mart appliances.” Indeed, it claims to have “invented the original appliance” — which is pretty close to being true.*
- Teradata claims its “new appliance easily delivers up to 5 to 10 times performance improvement over competitors’ appliances,” at $119,000 per terabyte US list price.
- Teradata claims a 150% faster “scan rate” than competitors. Teradata is surely thinking of Netezza when saying that.
- Teradata claims 10X performance improvement on “selected queries” vs. the “competition.”
- Teradata thinks its geospatial data management capability is better than competitors’, and that this is an important indicator of Teradata’s general overall greater sophistication.
| Categories: Analytic technologies, Data warehouse appliances, Data warehousing, GIS and geospatial, Netezza, Teradata | 4 Comments |
Known applications of MapReduce
Most of the actual MapReduce applications I’ve heard of fall into a few areas:
- Text tokenization, indexing, and search
- Creation of other kinds of data structures (e.g., graphs)
- Data mining and machine learning
That covers all MapReduce apps I recall hearing about via commercial companies and users, and also includes most of what’s in the two big sources I found online. Read more
| Categories: MapReduce, RDF and graphs, Text | 16 Comments |
Who is doing what in XML data management these days?
A comment thread to a post on a different subject has opened up a discussion of XML storage. Frankly, I haven’t kept up with my briefings on the subject, in part because XML support hasn’t proved to be very important yet to the big DBMS vendors, somewhat to my surprise. When last I looked, the situation wasn’t much different from what it was back in November, 2005. Unless I’ve missed something (and please tell me if I have!), here’s what’s going on: Read more
| Categories: IBM and DB2, Intersystems and Cache', MarkLogic, Microsoft and SQL*Server, Oracle, Structured documents | 7 Comments |
Detailed analysis of Perst and other in-memory object-oriented DBMS
Dan Weinreb — inspired by but not linking to my recent short post on McObject’s object-oriented in-memory DBMS Perst — has posted a detailed discussion of Perst on his own blog. For context, he compares it briefly to analogous products, most especially Progress’s — which used to be ObjectStore, of which Dan was the chief architect.
This was based on documentation and general sleuthing (Dan figured out who McObject got Perst from), rather than hands-on experience, so performance figures and the like aren’t validated. Still, if you’re interested in such technology, it’s a fascinating post.
| Categories: In-memory DBMS, McObject, Memory-centric data management, Object | Leave a Comment |
Open source in-memory DBMS
I’ve gotten email about two different open source in-memory DBMS products/projects. I don’t know much about either, but in case you care, here are some pointers to more info.
First, the McObject guys — who also sell a relational in-memory product — have an object-oriented, apparently Java-centric product called Perst. They’ve sent over various press releases about same, the details of which didn’t make much of an impression on me. (Upon review, I see that one of the main improvements they cite in Perst 3.0 is that they added 38 pages of documentation.)
Second, I just got email about something called CSQL Cache. You can read more about CSQL Cache here, if you’re willing to navigate some fractured English. CSQL’s SourceForge page is here. My impression is that CSQL Cache is an in-memory DBMS focused on, you guessed it, caching. It definitely seems to talk SQL, but possibly its native data model is of some other kind (there are references both to “file-based” and “network”.)
| Categories: Cache, DBMS product categories, In-memory DBMS, McObject, Memory-centric data management, Object, OLTP, Open source | 5 Comments |
McObject eXtremeDB — a solidDB alternative
McObject — vendor of memory-centric DBMS eXtremeDB — is a tiny, tiny company, without a development team of the size one would think needed to turn out one or more highly-reliable DBMS. So I haven’t spent a lot of time thinking about whether it’s a serious alternative to solidDB for embedded DBMS, e.g. in telecom equipment. However:
- IBM’s acquisition of Solid seems to suggest a focus on DB2 caching rather than the embedded market
- McObject actually has built up something of a customer list, as per the boilerplate on any of its press releases.
And they do seem to have some nice features, including Patricia tries (like solidDB), R-trees (for geospatial), and some kind of hybrid disk-centric/memory-centric operation.
| Categories: GIS and geospatial, In-memory DBMS, McObject, Memory-centric data management, solidDB | 6 Comments |
Database blades are not what they used to be
In which we bring you another instantiation of Monash’s First Law of Commercial Semantics: Bad jargon drives out good.
When Enterprise DB announced a partnership with Truviso for a “blade,” I naturally assumed they were using the term in a more-or-less standard way, and hence believed that it was more than a “Barney” press release.* Silly me. Rather than referring to something closely akin to “datablade,” EnterpriseDB’s “blade” program turns out to just to be a catchall set of partnerships.
*A “Barney” announcement is one whose entire content boils down to “I love you; you love me.”
According to EnterpriseDB CTO Bob Zurek, the main features of the “blade” program include: Read more