Browse to your KDiff3 install location for the executables.Check off to use the external compare tool as the default open action.Select Team -> Jazz Source Control -> External Compare Tools.Open the menu for Window -> Preferences.To configure KDiff3 in RTC perform the following steps: RTC allows a standalone merging tool to be used as a replacement of the internal one.
I have been using it to compare files for years.
It is GNU licensed which is ok for me but troubles our legal department -) Its installation is straight forward and it has direct Explorer integration on Windows systems.
It runs on MS-Windows, Mac OSX and any Un*x that is supported by QT. It works on single files and whole directories. Based on my experience and googling for 3-way merge, the following tools showed up in that particular order: KDiff3, P4Merge and DiffMerge.
So I looked for alternatives.Īn ideal merge tool would be free and should support all platforms. But recently I had to merge a branch with more than a year worth of changes (more than 1000 commits) and the RTC merge tool showed certain deficiencies which had a negative impact on my productivity. RTC has a built-in compare tool that works well for comparing files or reviewing changes and furthermore Jazz Version Control offers various ways to resolve conflicts.
Our contributions also include developing schema extraction strategies for schemaless systems of each NoSQL data model, and tackling performance and scalability in the implementation for each store." 3-way merges still remain one of the more taxing tasks of any software development team." (Wikipedia)įor my current work I use Rational Team Concert, an Eclipse based IDE. Our metamodel goes beyond the existing proposals by distinguishing entity types and relationship types, representing aggregation and reference relationships, and including the notion of structural variability. Through the paper, we will show how all these issues have been tackled in our approach.Īs far as we know, no proposal exists in the literature of a unified metamodel for relational and the NoSQL paradigms which describes how each individual data model is integrated and mapped. Moreover, data relationships supported by each data model are different For example, document stores have aggregate objects but not relationship types, whereas graph stores offer the opposite. Such an absence of schema declaration makes structural variability possible, i.e., stored data of the same entity type can have different structure. To achieve flexibility to respond to data changes, most of NoSQL systems are “schema-on-read,” and the declaration of schemas is not required. How these mappings have been implemented and validated will be discussed, and some applications of U-Schema will be shown. We will formally define the mappings between U-Schema and the data model defined for each database paradigm. In this paper, we present the U-Schema unified metamodel able to represent logical schemas for the four most popular NoSQL paradigms (columnar, document, key–value, and graph) as well as relational schemas. Also, the number of mappings required to migrate databases from a data model to another is reduced, and integrability is favored. Such metamodels facilitate developing database utilities, as they can be built on a common representation.
Multi-model database tools normally use a generic or unified metamodel to represent schemas of the data model that they support. Therefore, database tools and systems are evolving to support several data models. In this scenario, polyglot persistence is envisioned as the database architecture to be prevalent in the future. Although relational systems are still predominant, the interest in NoSQL systems is continuously increasing.
The Database field is undergoing significant changes.