Re: SQL3, Itasca, & UniSQL/X
Message-ID: <6143@unisql.UUCP>
Date: 10 Sep 93 14:26:04 GMT
References: <CD1Ln5.9G3@dcs.glasgow.ac.uk>
Organization: UniSQL, Inc., Austin, Texas, USA
>>...
For UniSQL/X, feel free to contact me (email, snail-mail or phone).
UniSQL/X is a SQL compliant database with Object Oriented extensions
(classes, inheritance, methods, etc). We have an information packet
available which includes a white-paper on our OORDMS approach.
Jon Higby
Technical Services Consultant
UniSQL, Inc.
9390 Research II, Suite 200
Austin, Texas 78759-6544
(512) 343-7297
*****************************************************************************
Standard disclaimer ... All opinions expressed are my own and not of my
employer.......................................
*****************************************************************************
> Versant (Versant Object Technology)
Versant is a client/server object database management system (ODBMS) targeted at
distributed, multi-user applications. Versant runs on UNIX and PC platforms,
including Sun, IBM, HP, DEC, SGI, Sequent, OS/2, with support for Windows NT is
planned during 1993.
Versant provides transparent language interfaces from object-oriented
programming languages such as C++ and Smalltalk. Versant also supports a C API.
Versant is built with an object-level architecture, which means that operations
are generally performed on the object (or group thereof) level. Key Versant
features include:
Performance
-----------
* Object-level locking for fine granularity concurrency control
* Server-based query processing to reduce network I/O
* Dual caching to speed warm traversals
* Dynamic space reclamation and reuse
Distribution
------------
* Immutable, logical object identifiers for data integrity
* Object migration (transparent relocation across nodes)
* Transparent cross-node references (distributed db)
* Automatic two-phase commit
Other
-----
* Schema evolution (online via lazy updates)
* Standard workgroup features (e.g., versioning, checkin/out)
* Detachable, personal databases
* DBA utilities
Additional information available from
info@versant.com (General information)
davek@versant.com (Dave Kellogg)
Versant Object Technology
1380 Willow Road
Menlo Park, California 94025
415-329-7500 phone.
415-325-2380 fax.
On Schema Evolution (from original survey):
We support run-time schema evolution. It uses a lazy scheme, so
schema operations are very fast. Objects on disk may have an older
`storage class' and they will be updated to the new schema when they
are used.
In older releases schema evolution was allowed only on leaf classes
(those with no subclasses). In our new release 2 (going to beta test
soon) you can do schema evolution on any class.
In the future we're working on more general view mechanisms so you can
see a subset of the attributes in memory, or some more complicated
transformation. This goes together with support for multiple
compilers and multiple languages.
[Joe Keane <osc!jgk@amd.com>]
Also: 1-800-Versant
Other Models
------------
Research Systems
________________
> GRAS
--------------------------------------------------------------
GRAS - A Graph-Oriented Database System for SE Applications
Copyright (C) 1987-1993 Lehrstuhl Informatik III, RWTH Aachen
--------------------------------------------------------------
See the GNU Library General Public License for copyright details.
Contact Adresses:
Dr. Andy Schuerr
Lehrstuhl fuer Informatik III,
University of Technology Aachen (RWTH Aachen),
Ahornstr. 55,
D-5100 Aachen
Email to
andy@i3.informatik.rwth-aachen.de
GRAS is a database system which has been designed according
to the requirements resulting from software engineering
applications. Software development environments are composed
of tools which operate on complex, highly structured data.
In order to model such data in a natural way, we have selected
attributed graphs as GRAS' underlying data model.
A first prototype of the GRAS (GRAph Storage) system - described
in /BL 85/ - was already realized in 1985. Since this time
gradually improving versions of the system have been used at
different sites within the software engineering projects
IPSEN /Na 90/, Rigi /MK 88/, MERLIN /DG 90/, and CADDY /EHH 89/.
Based on these experiences, almost all parts of the original
prototype have been redesigned and reimplemented.
Thus, nowadays a stable and efficiently working single-process
version of the system GRAS with interfaces for the programming
languages Modula-2 and C is available as free software for Sun
workstations (the GRAS system itself is implemented in Modula-2
and consists of many layers which might be reusable for the
implementation of other systems):
Via anonymous ftp from ftp.informatik.rwth-aachen.de
in directory /pub/unix/GRAS in file gras.<version-no>.tar.Z.
There are several files containing documentation, sources, binaries,
application examples, and libraries. All binaries are for Sun/4
machines. Sun/3 binaries are shipped only if explicitly requested.
You have to use the following sequence of operations for installing
the GRAS system at your site:
1) 'ftp ftp.informatik.rwth-aachen.de' (with login name "anonymous"
and password equal to your mail address).
2) 'cd pub/unix/GRAS' (for changing the current directory).
3) 'binary' (command for changing ftp mode).
4) 'get gras.<version-no.>' (use 'ls' for finding the currently used
GRAS version nr.).
5) 'bye' (for exiting ftp).
6) 'uncompress gras.<version-no>.tar'.
7) 'tar xvf gras.<version-no>.tar' (creates a subdirectory GRAS_2 for
the Modula-2 implementation of GRAS including its C-interface).
8) Follow the instructions in file GRAS_2/README.
The current version has programming interfaces for Modula-2 and C
and supports:
- the manipulation of persistent attributed, directed node- and
edge-labeled graphs (including the creation of very long
attributes and of attribute indexes).
- the manipulation of temporary/volatile generic sets/relations/lists,
- the coordination of graph accesses by different GRAS applications
(multiple-read/single-write access with graphs as lock units),
- error recovery based on shadow pages and forward logs,
- nested transactions and linear undo/redo of arbitrarily long
sequences of already committed graph modifying operations based
on forward and backward logs,
- event-handling (with certain kinds of graph-modifications
as events and graph-modifying transactions as event-handlers),
- primitives for version control comprising the capability
for efficiently storing graphs as forward/backward deltas to
other graphs,
- and primitives for declaring graph schemes and for incremental
evaluation of derived attributes.
Furthermore, tools for (un-)compressing graphs and a X11R5-based
graph browser are part of this release.
A multi-process version of the system GRAS supporting the inter-
action of multiple client and multiple server processes within
one local area network is nearby completion (version 6.0/0).
Thus, the GRAS system may be considered to be the core of a graph
oriented DBMS environment. The development of such an environment
based on a very high-level specifications language named PROGRES
is under way (the underlying calculus of this specifcation language
are so-called PROgrammed GRaph REwriting Systems).
This environment will comprise the following tools (a prerelease
of this environment might be made available upon request):
- a syntax-directed editor for graph schemes, graph rewrite rules,
and sequences of graph rewrite rules,
- an incrementally working consistency checker,
- an incrementally working compiler&interpreter translating
PROGRES specifications into sequences of GRAS procedure
calls (for C as well as for Modula-2),
- and an "enhanced" graph (scheme) browser.
References
----------
Refer to the following publications for further info about GRAS, PROGRES,
and related topics:
/BL85/ Brandes, Lewerentz: A Non-Standard Data Base System within
a Software Development Environment. In Proc. of the Workshop
on Software Engineering Environments for Programming-in-the-
Large, pp 113-121, Cape Cod, June 1985
/DHKPRS90/ Dewal, Hormann, Kelter, Platz, Roschewski, Schoepe: Evaluation
of Object Management Systems. Memorandum 44, University
Dortmund, March 1990
/Feye92/ Feye A.: Compilation of Path Expressions (in German), Diploma
Thesis, RWTH Aachen (1992)
/Hoefer92/ Hoefer F.: Incremental Attribute Evaluation for Graphs (in
German), Diploma Thesis, RWTH Aachen (1992)
/HPRS90/ Hormann, Platz, Roschweski, Schoepe: The Hypermodel Benchmark,
Description, Execution and Results. Memorandum 53, University
Dortmund, September 1990
/KSW92/ * Kiesel, Schuerr, Westfechtel: GRAS, A Graph-Oriented Database
System for (Software) Engineering Applications. Proc. CASE 93,
Lee, Reid, Jarzabek (eds.): Proc. CASE '93, 6th Int. Conf. on
Computer-Aided Software Engineering, IEEE Computer Society
Press (1993), pp 272-286
Also: Technical Report AIB 92-44,
/Klein92/ Klein P.: The PROGRES Graph Code Machine (in German), Diploma
Thesis, RWTH Aachen (1992)
/Kossing92/ Kossing P.: Modelling of Abstract Syntax Graphs for normalized
EBNFs (in German), Diploma Thesis, RWTH Aachen (1992)
/LS88/ Lewerentz, Schuerr: GRAS, a Management System for Graph-
Like Documents. In Proceedings of the Third International
Conference on Data and Knowledge Bases, Morgan Kaufmann
Publ. Inc. (1988), pp 19-31
/Nagl89/ Nagl (ed.): Proc. WG'89 Workshop on Graphtheoretic Concepts
in Computer Science, LNCS 411, Springer-Verlag (1989)
/NS91/ Nagl, Schuerr: A Specification Environment for Graph Grammars,
in Proc. 4th Int. Workshop on Graph-Grammars and Their
Application to Computer Science, LNCS 532, Springer-
Verlag 1991, pp 599-609
/Schuerr89/ Schuerr: Introduction to PROGRES, an Attribute Graph Grammar
Based Specification Language, in: /Nagl89/, pp 151-165
/Schuerr91a/ * Schuerr: PROGRES: A VHL-Language Based on Graph Grammars,
in Proc. 4th Int. Workshop on Graph-Grammars and Their
Application to Computer Science, LNCS 532, Springer-
Verlag 1991, pp 641-659
Also: Technical Report AIB 90-16
/Schuerr91b/ Schuerr: Operational Specifications with Programmed Graph
Rewriting Systems: Theory, Tools, and Applications,
Dissertation, Deutscher Universitaetsverlag (1991) (in German)
/SZ91/ * Schuerr, Zuendorf: Nondeterministic Control Structures for
Graph Rewriting Systems, in Proc. WG'91 Workshop in Graph-
theoretic Concepts in Computer Science, LNCS 570, Springer-
Verlag 1992, pp 48-62
Also: Technical Report AIB 91-17
/Westfe89/ Westfechtel: Extension of a Graph Storage for Software
Documents with Primitives for Undo/Redo and Revision Control.
Technical Report AIB Nr. 89-8, Aachen University of Technology,
1989
/Westfe91/ Westfechtel: Revisionskontrolle in einer integrierten Soft-
wareentwicklungsumgebung, Dissertation, RWTH Aachen, 1991
/Zuendorf89/ Zuendorf: Kontrollstrukturen fuer die Spezifikationssprache
PROGRES, Diplomarbeit, RWTH Aachen, 1989
/Zuendorf92/ * Zuendorf A.: Implementation of the Imperative/Rule Based
Language PROGRES, Technical Report AIB 92-38, RWTH Aachen,
Germany (1992)
/Zuendorf93/ * Zuendorf A.: A Heuristic Solution for the (Sub-) Graph
Isomorphism Problem in Executing PROGRES, Technical
Report AIB 93-5, RWTH Aachen, Germany (1993)
* : All reports marked with an asterisk are available via anonymous ftp from
ftp.informatik.rwth-aachen.de in directory /pub/reports/... .
See also PROGRES documentation.
[See also APPENDIX E]
> IRIS (HP Labs)
[Iris is a system out of HP Labs that began as a prototype and eventually
became a commercial product. I believe it was eventually incorporated into
the new HP product, OpenODB. - clamen]
Long and short system summaries can be found in:
[FISH89] D.H. Fishman et. al. Overview of the Iris DBMS. In Won.
Kim and Frederick H. Lochovsky, editors,
Object-Oriented Concepts, Databases and Applications,
chapter 10, pages 219--250. Addison-Wesley, Reading,
MA, 1989.
[FBC+87] D.H. Fishman, D. Beech, H.P. Cate, E.C. Chow,
T. Connors, J.W. Davis, N. Derrett, C.G. Hock, W. Kent,
P. Lyngbaek, B. Mahbod, M.A. Neimat, T.A. Tyan, and
M.C. Shan. Iris: An object-oriented database
management system. ACM Transactions on Office
Information Systems, 5(1):48--69, January 1987.
The abstract of the latter (written early in the project) follows:
The Iris database management system is a research prototype of
a next-generation database management system intended to meet
the needs of new and emerging database applications, including
office automation and knowledge-based systems, engineering
test and measurement, and hardware and software design. Iris
is exploring a rich set of new database capabilities required
by these applications, including rich data-modeling
constructs, direct database support for inference, novel and
extensible data types, for example to support graphic images,
voice, text, vectors, and matrices, support for long
transactions spanning minutes to many days, and multiple
versions of data. These capabilities are, in addition to the
usual support for permanence of data, controlled sharing,
backup and recovery.
The Iris DBMS consists of (1) a query processor that
implements the Iris object-oriented data model, (2) a
Relational Storage Subsystem (RSS) -like storage manager that
provides access paths and concurrency control, backup and
recovery, and (3) a collection of programmatic and interactive
interfaces. The data model supports high-level structural
abstractions, such as classification, generalization, and
aggregation, as well as behavioral abstractions. The
interfaces to Iris include an object-oriented extension to
SQL.
On Schema Evolution (from original survey):
Objects in the Iris system may acquire or lose types dynamically.
Thus, if an object no longer matches a changed definition, the user
can choose to remove the type from the object instead of modifying the
object to match the type. In general, Iris tends to restrict class
modifications so that object modifications are not necessary. For
example, a class cannot be removed unless it has no instances and new
supertype-subtype relationships cannot be established.
Commercial Systems
__________________
> IDL (Persistent Data Systems)
IDL is a schema definition language. Schema modifications are defined
in IDL, requiring ad-hoc offline transformations of the database, in
general. A simple class of transformations can be handled by
IDL->ASCII and ASCII->IDL translators (i.e., integer format changes,
list->array, attribute addition).
[conversation with Ellen Borison of Persistent Data Systems]
ADDITIONAL REFERENCES:
John R. Nestor. "IDL: The Language and Its
Implementation". Prentice Hall. Englewood Cliffs,
NJ., 1989.
> Kala
Kala Technical Brief
Summary
Kala(tm) is a Persistent Data Server managing distributed, shared,
arbitrarily complex and evolving persistent data. Kala is highly
efficient and secure. Kala manages the visibility of persistent data
elements to its clients, thus supporting any types of transactions,
versions, access control, security, configurations. Kala does not
restrict you to any particular model. Kala provides the mechanism, but
imposes no policy. Usable as either a link library communicating to a
server or as a standalone, Kala is compact and simple.
Kala is used for applications such as: kernel of DBMS products,
substrate for extended file systems, implementation of language
persistence, data manager for groupware applications as well as
applications which deal with large, complex, and changing volumes of
data (text databases, financial distributed transaction systems). Our
current customers use Kala in applications ranging from CASE
repositories to CAD systems, from document management for financial
institutions to OODBMS platforms, from real-time applications to
database research. Kala is a component of broad reuse.
Motivation
The simplest persistent data storage available to you is the file
system on your disk drive. File systems have some attractive
characteristics; their performance is good, they can hold any data,
they're easy to use, and, of course, the price is right. Conversely,
files are unreliable. They provide no mechanism for in maintaining
data consistency and only primitive data sharing facilities. Few file
systems offer version control and all require that you transform data
between "internal" and "external" forms all the time.
Unlike a file system, a true database management system provides
mechanisms for sharing data and for ensuring the integrity of the
data. It supports transactions and version control, although the
specifics of these functions may not be exactly what your application
needs. Finally, a database system is scalable, and much more robust
than a file when your hardware or software fails.
The downside to a database system is that, compared to a file system,
it is slower by an order of magnitude or more. Also, a database system
generally confines you to dealing only with the kind of data that it
can handle. In addition, a database is usually very complicated,
difficult to learn and use, and expensive, both in terms of your cost
of operation and in the amount of system resources they consume.
Whether you choose a file system or a database manager, then, you
have to sacrifice either economy or performance. Is there a happy
medium? Something with the speed and flexibility of files, the
reliability, shareability and robustness of databases, and at a cost
that won't break your wallet or the available hardware? Sure there is!
Kala is a first in a new breed of products, persistent data servers,
aimed squarely at the yawning gap between DBMSs and file systems.
Overview
Kala is *not* a DBMS. Instead, you use Kala whenever the few canned
combinations of DBMS features do not meet the needs of your
application. A DBMS product constrains you to accept *its* choice of
an end-user graphical interface, a query language binding, a specific
high level data or object model, a particular transaction model, a
single versioning scheme, etc. This either compromises your
application's functionality, or forces your to spend substantial
development effort and money to bridge the impedance mismatch to the
application. Instead, Kala allows *you* to develop no more and no
less than the functionality you need. You build your domain specific
functionality our of a small set of primitives with very little code.
Your gains in productivity, efficiency, and flexibility are
substantial.
To sustain this level of flexibility and reuse, Kala manages any data
that you can represent in machine memory out of bits and references.
Examples include records, dynamically linked graphs and lists,
executable code, and object encapsulations.
Kala can handle data as small as one bit, and as large as the virtual
memory and more, while being totally unaware of the data's semantics.
Its stores and retrieves data efficiently, and compactly over a
distributed and dynamically reconfigurable set of Stores. Upon
retrieval, Kala dynamically relocates embedded references to retain
the original topological structure of the data, thus preserving
referential integrity. Kala also supports active data, physical store
management, and automatic archiving.
Kala repackages the fundamentals and universals of data management in
one reusable data server, separating them from the application domain
specific models and policies. Kala defines a low level interoperabi-
lity point for the data storage domain, just as X does for the display
domain and Postscript does for the printing domain.
Kala has matured through four successive versions to its present
industrial strength implementation and stable API. Kala is lean,
compact, and portable. Kala is a high performance, low overhead
system. We call it a Reduced Instruction Set Engine (RISE). Unlike
large, complex, and typically bulky DBMS products, Kala is small,
simple, and suitable for managing anywhere from a single diskette to
terabytes of distributed data.
Benefits
* For those who need functionality traditionally associated with
databases, but cannot tolerate the overhead and complications DBMS
products introduce, Kala offers a flexible, compact, performant,
elegant, and simple alternative.
* For those whose application domain requires data models where the
mapping to those offered by today's DBMS products is cumbersome,
introduces development and execution overhead, and is not portable
across multiple linguistic and environmental platforms, Kala offers
a data model independent interface against any data model
expressible in terms of bits and pointers can be easily built.
* For those who need DBMS functionality or qualities that no single
DBMS product now has, Kala offers the opportunity to build that
functionality now with little effort out of a simple set of
primitives, and not wait for one vendor or another to deliver
it later.
* For those who have determined that the only viable option for their
application's persistent data needs is the file system, and have
resined to the idea that they will have to build everything else
they need from scratch, Kala offers an off-the-shelf implementation
without loss of any of files' advantages.
* For those who need performance, size, portability, storage
compactness, and industrial strength that no single DBMS product can
now satisfy, Kala offers all of the above now.
* For those who realize that while object-level interoperability is a
strong desideratum, the likelihood of a single, universal such model
in the foreseeable future is quite low, Kala offers a solid, long
term alternative. Data store interoperability that brings us beyond
file systems is the best practical bet. Kala is the basis for data
store interoperability now.
* Finally, for all of you who are concerned about the economics of
software, and take the view that there are many elements that
could contribute negatively to the soundness of your business, such
as operational costs, software maintenance costs, software licensing
costs, software development and learning costs, etc., you will find
Kala an economically sound, sensible, and practical product.
Features
- The execution architecture is that of multiple (communicating)
servers and multiple clients. Kala can also be configured in a
standalone (single process) mode. Kala's IPC is built for maximum
performance, portable to any given datagram protocol.
- The managed data elements are made out of uninterpreted bits and
references. Data elements (named `monads') are universally uniquely
identified. Bits are stored with no overhead. References,
represented in memory as native machine pointers, are stored
very compactly, introducing an average of 2.5 bytes overhead.
- Kala is a fully recoverable system, short of media damage. Recovery
from hardware failures can be supported by the layer beneath Kala.
- The Kala primitives support arbitrary transaction models, including
classic short transactions, long (persistent) transactions, nested
transactions, shared transactions, pessimistic and optimistic
policies, etc. Concurrency control is achieved through two locking
mechanisms (short-term and long-term (persistent, shared) locking),
with full support for atomicity of operations and two-phase commit.
- The Kala primitives support arbitrary versioning models, allowing
versions to co-exist in split/rejoined networks, various version
organization strategies (single-thread, tree, DAG, etc.). Kala
primitives provide mechanisms for arbitrary access and update
triggers, such as notifications, security checks upon access/update,
etc. __ with no limitations on what the trigger code does. Kala
provides protection measures against virus and other intruding
executions.
- The Kala primitives support a wide range of access control, security
and protection models, including revocable access rights, access
control without the overhead of ACL management, arbitrary access
validation routines, etc. Kala does not introduce any more security
holes than the operating environment already has.
- Kala has primitives for physical store allocation and de-allocation
management, for a wide spectrum of store administrative tasks, as
well as licensing administration. The latter includes application-
sensitive time-limited client-connect-based licensing, as well as
metered (connect/load/store) usage. Kala can be set up to do
automatic archiving and backup of its physical store.
- Kala provides a wide spectrum of licensing schemes, usable by
platforms and applications built upon Kala to their customer base.
Kala provides renewable licenses, perpetual licenses, full
protection against duplication without hardware (hostid) support,
metered (pay-by-use) usage, etc.
- And more ... not fitting on this page-long Technical Brief.
Availability
o Kala is available now on Sun platforms (SunOS / 68K & SPARC), as
well as on 80x86/MS-DOS (both Microsoft and Borland compilers &
runtimes supported) platforms. If you are interested in a port to
your favorite platform, call us to discuss our Development and
Porting Partnership Programme.
o Kala's interface is ANSI C, also callable from C++. If you are
interested in an interface or a binding to your favorite programming
language, please call us to discuss out Development Partnership
Programme.
o For pricing and other information, please contact us by phone, fax
or via e-mail at Info@Kala.com
_ _ ____ _ ____ tm ____________________________________
\\ / | \ \ | \ \\\\
\\ /__ \ __ \ \ \ __ \ \\\\
\\ \ \ \ \ \ \ \\\\
\\ \ \ \ \ \ \ \\\\ No more than you need !!!
\\' \' \' \' '____' \' \' \\\\ No less than you want !!!
........................................................................
Penobscot Development Corporation email: Info@Kala.com
One Kendall Square Building 200 Suite 2200 Cambridge MA 02139-1564 USA
voice +1-617-267-KALA fax +1-617-859-9597 tech support +1-201-539-7739
...............(5252) fax +1-617-577-1209.............................
+---------------------------------------------------------------+
| Copyright (c) 1992-93, Penobscot Development Corporation. |
| Kala is a Trademark of Penobscot Development Corporation. |
+---------------------------------------------------------------+
On Schema Evolution (from original survey):
Kala manages an untyped persistent store, implementing the semantics
of robust, distributed, secure, changing, and shareable persistent
data. Layers built upon the Kala platform can implement the semantics
of objects with the same properties.
As it operates below the schema layer, Kala does not address schema
evolution directly. However, It supports the building of schema'ed
layers above it and below the application, and those layers can
provide for schema evolution conveniently using Kala primitives.
This parts-box approach requires extra work on the part of the developer
compared to out-of-the-box solutions, but provides power and
flexibility sufficient for relatively low cost solutions in
difficult environments (e.g. graph-structured data, dynamic classing)
where no out-of-the-box solution is available.
Contacts:
Sergiu Simmel sss@kala.com
Ivan Godard ig@kala.com
general information info@kala.com
subscription to moderated newsletter forum-request@kala.com
REFERENCES:
Segui S. Simmel and Ivan Godard. "The Kala Basket: A
Semantic Primitive Unifying Object Transactions,
Access Control, Versions, annd Configurations
> Pick
With Pick and its variants you only have problems if you want to
redefine an existing field. Because of the way the data are stored
and the separation of the data and the dictionary you can define
additional fields in the dictionary without having to do anything to
the data - a facility which we have found very useful in a number of
systems.
There is no general facility to redefine an existing field - you just
make whatever changes are required in the dictionary then write an
Info Basic program to change the data. We have seldom needed to do
this, but it has not been complicated to do.
If a field in the database is no longer used, it is often easiest
simply to delete the reference to that field in the dictionary, and
accept the storage overhead of the unused data. In such cases, while
the data cannot be accessed through the query language, (Pick)Basic
programs can still access them.
[Geoff Miller <ghm@ccadfa.cc.adfa.oz.au>]
Interfaces
----------
Research Systems
________________
> Penguin (Stanford)
Penguin is an object-oriented interface to relational databases.
Penguin has its own simple language-independent object model with
inheritance for composite objects defined as views (called
view-objects) of a relational database. These view-objects represent
data according to application requirements in such a way that multiple
applications can share overlapping, but different, sets of data.
Multiple applications may share data by having overlapping schemata
with differing composite objects and differing inheritance mappings.
We have a C++ binding, which supports multiple inheritance. The
result is a framework for collaboration among multiple users, each
with differing perspectives about the system and its data.
For additional information, please contact ark@db.stanford.edu
References:
``A C++ Binding for Penguin: a System for Data Sharing among
Heterogeneous Object Models,'' Arthur M. Keller, Catherine Hamon,
Foundations on Data Organization (FODO) 93, October 1993, Chicago.
``Querying Heterogeneous Object Views of a Relational Database,''
Tetsuya Takahashi and Arthur M. Keller, Int. Symp. on Next Generation
Database Systems and their applications, Fukuoka, Japan, September
1993, to appear.
``Updating Relational Databases through Object-Based Views,'' by
Thierry Barsalou, Niki Siambela, Arthur M. Keller, and Gio Wiederhold,
ACM SIGMOD, Denver, CO, May 1991.
``Unifying Database and Programming Language Concepts Using the Object
Model'' (extended abstract), Arthur M. Keller, Int. Workshop on
Object-Oriented Database Systems, IEEE Computer Society, Pacific
Grove, CA, September 1986.
Commercial Systems
__________________
> Persistence
PERSISTENCE(TM): BRIDGING THE GAP BETWEEN OBJECT
ORIENTED DEVELOPMENT AND RELATIONAL DATA
Persistence is an application development tool which provides object
oriented access to existing relational data. Persistence uses an
automatic code generator to convert object models into C++ classes
which know how to read and write themselves to a relational database.
Leverage existing data
Persistence enables object oriented access to existing relational
databases. Applications built with Persistence can work side by side
with legacy systems.
Automate database access
By generating the methods to convert relational data into objects,
Persistence saves the developer from having to write literally hundreds
of lines of code per class.
Speed application development
With Persistence, major changes to the application object model can be
completed in minutes, not weeks.
Quality
Persistence generates tested, bug-free code. Using Persistence helps
ensure the reliability and reusability of your applications.
Performance
At Runtime, Persistence manages an object cache to enhance performance
while ensuring data integrity. The Persistence object cache can provide
a factor of ten performance improvement for data intensive
applications.
Portability
Code generated by Persistence is database independent. You can choose
which database to work with at link step, increasing application
portability.
TECHNICAL SPECIFICATIONS
The Persistence Database Interface Generator converts object schemas
into C++ classes.
Custom
Code
|
v
Object schema ---> Persistence ----> Generated
Generator Classes
^
|
v
Persistence
Object Cache
^
|
v
Legacy Data
Encapsulation
Each class generated by Persistence maps to a table or view in the database.
- Query using ANSI SQL or attribute values
- Add custom code to generated classes
- Preserve custom code when model changes
Inheritance
Persistence supports inheritance of attributes, methods and relationships.
- Propagate superclass queries to subclasses
- Use virtual methods for polymorphism
Associations
Persistence maps associations to foreign keys in the database. Each class has methods to access related classes.
- Ensure referential integrity between classes
- Specify delete constraints for associations
Object Caching
The Persistence Runtime Object Management System caches objects during
transactions and ensures data integrity. In the object cache,
Persistence "swizzles" foreign key attributes into in-memory pointers,
speeding object traversal.
Transactions
When a transaction is committed, Persistence walks through the object
cache and writes out changes to the database.
Environment
Platforms/Operating systems
Persistence will support all major Unix and Intel platforms
- Sun/SunOS 4.x, Solaris 2.x
- HP/HP-UX 8.0, 9.0
- IBM/AIX (planned 11/93)
- Intel/NT (planned 3/94)
Development Tools
Persistence supports all major C++ compilers and integrates with GE's
OMTool, allowing developers to go straight from an object model to a
running C++ application.
- Cfront 2.1: ObjectCenter 1.0, SPARCompiler, ObjectWorks
- Cfront 3.0: ObjectCenter 2.0, SPARCompiler, Softbench C++
- GE's OMTool
Databases
Persistence provides database independence. With our Objectivity
integration, we also provide a clear migration path to object
databases.
- Oracle V6, V7
- Sybase 4.x
- Ingres 6.x
- Objectivity ODBMS
- Informix (planned 9/93)
- ODBC (planned 3/94)
CUSTOMER QUOTES
"We wanted to use object technology while continuing to support our
legacy systems. Persistence made this feasible by automating over 30
percent of our development cycle." Steve Hunter, Sterling Software
"Persistence cut our development time by approximately 40%, because we
would have had to do all the mapping functions ourselves." Jim
Adamczyk, Partner, Andersen Consulting
"I'm convinced we'll save weeks or months of time because of
Persistence." Mike Kubicar, SunSoft Defect Tracking Team
"The good thing is that you can change your object model and just
re-generate the database interface classes at the press of a button."
Richard Browett, Product manager, K2 Software Developments, Ltd.
"The Persistence package saved at least 25 to 50 percent of the
development time, and seemed extremely robust. Support has been nothing
short of phenomenal." Stew Schiffman, DuPont Research and Development
FOR MORE INFORMATION
For more information on Persistence, please contact Carl White, VP Sales:
- By phone: (415) 341-1280
- By fax: (415) 341-8432
- By email: information@persistence.com
Persistent Data Systems
PO Box 38415
Pittsburgh, PA 15238-9925
> Subtlware
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