Cost-Based Optimization of Integration Flows - Datenbanken ...

2 Preliminaries and Existing Techniques
Due to these goals of integration that are based on different application use cases,
a variety of integration approaches and realizations emerged in the past. In order to
precisely separate the focus of this thesis, we classify those integration approaches, where
integration flows are only one category among others.
2.1.1 Classification of Integration Approaches
There exist several, partially overlapping, classification aspects of integration approaches,
which include the (1) application area, (2) data location, (3) time aspect and consistency
model, (4) event model, (5) topology, and (6) specification method. We explicitly exclude
orthogonal integration aspects such as schema matching, model management, master data
management, lineage tracing and the integration of semi-structured and unstructured data
because techniques from these areas are typically not specifically designed for a certain
integration approach.
Integration
Application
Area
GUI
Integration
Process
Integration
Application
Integration
Information
Integration
Data
Location
virtual materialized
materialized materialized virtual
System
Aspect
Portals Mashups WfMS WSMS BPEL
Engines
EAI
servers
MOM
systems
ETL
Tools
Publish/
Subscribe
DSMS
PDMS VDBMS/
FDBMS
Specification
Method
User-Interface-Oriented
Integration Flows
Query-Based
Figure 2.1: Classification of Integration Approaches
Our overall classification that is shown in Figure 2.1 comprises the aspects (1) application
area, (2) data location, and (6) specification method. In addition, we put the major types
of integration systems (system aspect) into the context of this classification. Regarding
the application area, we distinguish between information integration (data and function
integration), application integration, process integration and GUI integration.
Information integration refers to the area of data-centric integration approaches, where
huge amounts of data are integrated. In this context, we typically distinguish between
virtual and materialized integration [DD99] based on the data location. First, for virtual
integration, a global (virtual) view over the distributed data sources is provided and
data is not physically consolidated. Examples for this type of integration approach are
virtual DBMS (VDBMS), federated DBMS (FDBMS), and Peer Database Management
Systems (PDBMS). The difference is that VDBMS/FDBMS use a hierarchical topology,
while PDBMS use a peer-to-peer topology. Typically, both system types provide an event
model of ad-hoc queries in order to allow dynamic integration. Second, for materialized
integration, the data is physically stored or exchanged with the aim of data consolidation
or synchronization. In this context, we mainly distinguish two types of system categories
based on their event model. On the one side, DSMS (Data Stream Management Systems)
and Publish/Subscribe systems follow a data-driven model where tuples are processed
by standing queries or subscription trees, respectively. While DSMS execute many rather
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