Object

Analysis of data management technology optimized for object data. Related subjects include:

August 26, 2010

More on NoSQL and HVSP (or OLRP)

Since posting last Wednesday morning that I’m looking into NoSQL and HVSP, I’ve had a lot of conversations, including with (among others):

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August 22, 2010

Workday comments on its database architecture

In my discussion of Workday’s technology, I gave an estimate that Workday’s database, if relationally designed, would require “1000s” of tables. That estimate came from Workday, Inc. CTO Stan Swete, in a thoughtful email that made several points about Workday’s database strategy. Workday kindly gave me permission to quote it below.
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August 22, 2010

The Workday architecture — a new kind of OLTP software stack

One of my coolest company visits in some time was to SaaS (Software as a Service) vendor Workday, Inc., earlier this month. Reasons included:

Workday kindly allowed me to post this Workday slide deck. Otherwise, I’ve split out a quick Workday, Inc. company overview into a separate post.

The biggie for me was the data and object management part. Specifically:  Read more

June 19, 2010

Objectivity Infinite Graph

I chatted Wednesday night with Darren Wood, the Australia-based lead developer of Objectivity’s Infinite Graph database product. Background includes:

Infinite Graph is an API or language binding on top of Objectivity that:

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April 3, 2010

Akiban highlights

Akiban responded quickly to my complaints about its communication style, and I chatted for a couple of hours with senior Akiban techies Ori Herrnstadt, Peter Beaman and Jack Orenstein. It’s still early days for Akiban product development, so some details haven’t been determined yet, and others I just haven’t yet pinned down. Still, I know a lot more than I did a day ago. Highlights of my talk with Akiban included: Read more

January 15, 2010

Intersystems Cache’ highlights

I talked with Robert Nagle of Intersystems last week, and it went better than at least one other Intersystems briefing I’ve had. Intersystems’ main product is Cache’, an object-oriented DBMS introduced in 1997 (before that Intersystems was focused on the fourth-generation programming language M, renamed from MUMPS). Unlike most other OODBMS, Cache’ is used for a lot of stuff one would think an RDBMS would be used for, across all sorts of industries. That said, there’s a distinct health-care focus to Intersystems, in that:

Note: Intersystems Cache’ is sold mainly through VARs (Value-Added Resellers), aka ISVs/OEMs. I.e., it’s sold by people who write applications on top of it.

So far as I understand – and this is still pretty vague and apt to be partially erroneous – the Intersystems Cache’ technical story goes something like this: Read more

June 8, 2008

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.

June 6, 2008

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”.)

February 1, 2008

Dan Weinreb on ObjectStore

Dan Weinreb was one of the key techies at Object Design, the company that made the object-oriented database management system ObjectStore. (Object Design later merger into Excelon, which was eventually sold to Progress, which has deemphasized but still supports ObjectStore.) Recently he wrote a pair of long and fascinating articles about Object Design, ObjectStore, and OODBMS, the first of which makes the case that “object-oriented database management systems succeeded.” Read more

January 27, 2008

The 4 main approaches to datatype extensibility

Based on a variety of conversations – including some of the flames about my recent confession that mid-range DBMS aren’t suitable for everything — it seems as if a quick primer may be in order on the subject of datatype support. So here goes.

“Database management” usually deals with numeric or alphabetical data – i.e., the kind of stuff that goes nicely into tables. It commonly has a natural one-dimensional sort order, which is very useful for sort/merge joins, b-tree indexes, and the like. This kind of tabular data is what relational database management systems were invented for.

But ever more, there are important datatypes beyond character strings, numbers and dates. Leaving out generic BLOBs and CLOBs (Binary/Character Large OBjects), the big four surely are:

Numerous other datatypes are important as well, with the top runners-up probably being images, sound, video, time series (even though they’re numeric, they benefit from special handling).

Four major ways have evolved to manage data of non-tabular datatype, either on their own or within an essentially relational data management environment. Read more

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