Object
Analysis of data management technology optimized for object data. Related subjects include:
- Native XML database management
- Intersystems, vendor of the Cache’ object-oriented DBMS
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):
- Dwight Merriman of 10gen (MongoDB)
- Damien Katz of Couchio (CouchDB)
- Matt Pfeil of Riptano (Cassandra)
- Todd Lipcon of Cloudera (HBase committer)
- Tony Falco of Basho (Riak)
- John Busch of Schooner
- Ori Herrnstadt of Akiban
| Categories: Akiban, Basho and Riak, Cache, Cassandra, Cloudera, Clustrix, CouchDB, Facebook, HBase, Hadoop, MySQL, NoSQL, OLTP, Object, Open source, Parallelization, Riptano, Schooner, Theory and architecture, Tokutek, memcached | Leave a Comment |
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.
Read more
| Categories: Data models and architecture, OLTP, Object, Software as a Service (SaaS), Specific users, Theory and architecture, Workday | 2 Comments |
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 has forward-thinking ideas about SaaS enterprise applications and the integration of business intelligence into same.
- Workday has highly innovative ideas in how it manages data.
- Companies founded by Dave Duffield tend to feature smart, likeable people who talk to one pleasantly and forthrightly. Workday is no exception; CTO Stan Swete and the other Workday folks present were a delight to talk with.
- I’d invited Merv Adrian to come along with me. He asked great questions, and I could gather myself a bit despite how sleep-deprived I was for the first part of that trip.
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
Objectivity Infinite Graph
I chatted Wednesday night with Darren Wood, the Australia-based lead developer of Objectivity’s Infinite Graph database product. Background includes:
- Objectivity is a profitable, decades-old object-oriented DBMS vendor with about 50 employees.
- Like some other object-oriented DBMS of its generation, Objectivity is as much a toolkit for building DBMS as it is a real finished DBMS product. Objectivity sales are typically for custom deals, where Objectivity helps with the programming.
- The way Objectivity works is basically:
- You manage objects in memory, in the format of your choice.
- Objectivity bangs them to disk, across a network.
- Objectivity manages the (distributed) pointers to the objects.
- You can, if you choose, hard code exactly which objects are banged to which node.
- Objectivity’s DML for reading data is very different from Objectivity’s DML for writing data. (I think the latter is more like the program code itself, while the former is more like regular DML.)
- The point of Objectivity is not so much to have fast I/O. Rather, it is to minimize the CPU cost of getting the data that comes across the wire into useful form.
- Darren got the idea of putting a generic graph DBMS front-end on Objectivity while doing a relationship analytics project for an Australian intelligence agency.
- Darren redoubled his efforts to sell the project internally at Objectivity after reading what I wrote about relationship analytics back in 2006 or so.
- There is now a 5 or so person team developing Infinite Graph.
- Infinite Graph is just now going out to beta test.
Infinite Graph is an API or language binding on top of Objectivity that:
- Hides a lot of Objectivity’s complexity.
- Is suitable for graph/relationship analytics.
| Categories: Analytic technologies, Liberty and privacy, Object, Objectivity and Infinite Graph, RDF and graphs | 5 Comments |
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
| Categories: Akiban, MySQL, OLTP, Object, Software as a Service (SaaS) | 4 Comments |
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:
- MUMPS, the original Intersystems technology, was focused on health care.
- The reasons Intersystems went object-oriented have a lot to do with the structure of health-care records.
- Intersystems’ biggest and most visible ISVs are in the health-care area.
- Intersystems is actually beginning to sell an electronic health records system called TrakCare around the world (but not in the US, where it has lots of large competitive VARs).
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
| Categories: Data models and architecture, Emulation, transparency, portability, Intersystems and Cache', Mid-range, OLTP, Object, Sybase, Theory and architecture | 3 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, OLTP, Object, Open source | 5 Comments |
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
| Categories: Object, Progress, Apama, and DataDirect | Leave a Comment |
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:
- Text. Text search is a huge business on the web, and a separate big business in enterprises. And text doesn’t fit well into the relational paradigm at all.
- Geospatial. Information about locations on the earth’s surface is essentially two-dimensional. Some geospatial apps use three dimensions.
- Object. There are two main reasons for using object datatypes. First, the data can have complex internal structures. Second, it can comprise a variety of simpler types. Object structures are well-suited for engineering and medical applications.
- XML. A great deal of XML is, at its heart, either relational/tabular data or text documents. Still, there are a variety of applications for which the most natural datatype truly is XML.
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
| Categories: Data types, GIS and geospatial, Object, Structured documents, Text | 10 Comments |