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Embedding¶ To de-normalize data, store two related pieces of data in a single document. Operations within a document are less expensive for the server than operations that involve multiple documents. In general, use embedded data models when: you have “contains” relationships between entities. See Model Embedded One-to-One Relationships Between Documents. you have one-to-many relationships where the “many” objects always appear with or are viewed in the context of their parent documents. See Model Embedded One-to-Many Relationships Between Documents. Embedding provides the following benefits: generally better performance for read operations. the ability to request and retrieve related data in a single database operation.

Referencing¶ To normalize data, store references between two documents to indicate a relationship between the data represented in each document. In general, use normalized data models: when embedding would result in duplication of data but would not provide sufficient read performance advantages to outweigh the implications of the duplication. to represent more complex many-to-many relationships. to model large hierarchical data sets. See Model Tree Structures in MongoDB. Referencing provides more flexibility than embedding; however, to resolve the references, client-side applications must issue follow-up queries. In other words, using references requires more roundtrips to the server.

QLDoc Sharp is an interactive tool designed to generate the SQL Server 2005/2008 documentation. It allows you to export documentation to CHM format (Microsoft Compiled HTML Help).It is also easy and interactive, which allows multiple database documentation. For more details, please refer to http://www.amitchaudhary.com/. Background Finding the answer to, "Is there any free tool for generating documentation from SQL 2005/2008". Using the Code After running the application, the initial UI looks like below: Three steps required to generate the documentation. Step # 1 In the top section, provide the details about the SQL Server. It includes: Source: Instance Name of the SQL Server 2005/2008  If want to connect with SQL authentication then: User Name: Name of the user whose credentials you want to use Password: Password of the user whose credentials you want to use In case, to connect with Windows authentication then, only check the checkbox   (Integrated Security) and your current Windows credentials would be used to connect with the specified SQL Server Instance. Step # 2 Choose the database name from the Database dropdown list, whose documentation you want to generate and then click on the Fetch button. Meanwhile you can choose/change the File Name of the CHM file which would be generated. And also if required, you then choose to export the metadata/documentation in the XML format too. Step # 3 Click on the Generate button. And locate the CHM file at the path specified. After making the selection the SQLDoc Sharp, the UI should look like: Screen Shots of the Documentation Generated Index

SQLDoc Sharp is an interactive tool designed to generate the SQL Server 2005/2008 documentation.

Versioning is an extra-feature that is not fundamental to document databases. MongoDB and CouchDB do not support it by default, but there are different solutions available

Versioning is not supported by either MongoDB and CouchDB. MVCC should not be confused for document versioning

Built-in Versioning: Most document databases support versioning of documents with the flip of a switch.

Placing a document under version control is very unintrusive. Vermongo only adds a version number property (an int32 called _version) to the document. It does not touch any other fields. In particular, it also does not place any requirements on the contents of the _id field. Older revisions are stored in a separate collection that shadows the original collection. They are MongoDB documents themselves, and can be queried.

When creating, updating, or deleting documents, you just have to follow the Vermongo protocol outlined here. There will be (at least) a Java library to facilitate this. The only major downside is that documents have to be updated one-by-one (no bulk updates possible), and that there is some overhead in retrieving and copying the old version. Query operations can just proceed as normal.

After inserting into collection 'foo' a document { a=>"x"}, updating it to { a: "y"}, then to { a: "z" }, and finally deleting it, the shadow collection will contain the following (the original collection will not contain the document anymore, as it has been deleted): > db.foo.vermongo.find() { "_id" : { "_id" : ObjectId("4c78da..."), "_version" : 1 }, "a" : "x", "_version" : 1 } { "_id" : { "_id" : ObjectId("4c78da..."), "_version" : 2 }, "a" : "y", "_version" : 2 } { "_id" : { "_id" : ObjectId("4c78da..."), "_version" : 3 }, "a" : "z", "_version" : 3 } { "_id" : { "_id" : ObjectId("4c78da..."), "_version" : 4 }, "_version" : "deleted:4" }

Document a database in a couple of clicks, from within SSMS

you can add further descriptions to your database objects if necessary.

There are several common strategies for document versioning. The strategy you select will depend on the trade-offs you want to make. Please note that MongoDB does not have any support for triggers. So a few of these methods will require that you be able to do multiple writes.

=== Strategy 1: embed history === In theory, you can embed the history of a document inside of the document itself. This can even be done atomically.

=== Strategy 2: write history to separate collection ===

It's more typical to keep older versions of your document inside your current revision (either as JSON or, often, as an attachment). For the JSON case; { "_id":"foo", "_rev":"3-fsfsfsdf", "foo":"current value of foo", "history": { "2": { "foo":"previous version of foo" }, "1": { "foo":"initial version of foo" } } }

t's often simpler to push the full old version of the document into an attachment instead. This pattern is common enough that CouchDB ships with a library, jquery.couch.js, that implements it (in the saveDoc(doc) function).

This article will help to choose a proper SQL XML Documentation format for the future and help to convert these comments into Microsoft Help formats with minimal resources.

Microsoft SandCastle Command Line Interface (CLI) Tool used for creating MSDN-style documentation from .NET assemblies and their associated XML comments files. CodePlex SandCastle Help File Builder Graphical User Interface (GUI) for Microsoft SandCastle. Also contains command line based tools to build a help file in an automated fashion.

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I agree with core developers, that there is no need for that to be implemented inside JsTestDriver. Everybody has slightly different needs and this would make configuration complicated. It is easy to solve in JavaScript: * request HTML page with XMLHttpRequest * extract body * inject into the body of the document under test req = new XMLHttpRequest(); req.open('GET', url, false); /* synchronous */ req.send(null); /* body element with children */ body_content = req.responseText.match(/<body[\s\S]*<\/body>/); body = document.documentElement.getElementsByTagName('body')[0]; /* body tag itself is ignored, only its children will be inserted */ body.innerHTML = body_content; } I've documented the full solution at http://www.mobile-web-consulting.de/post/4720306582/jstestdriver-html-injection-from-separate-file

{ _id: ..., public: true, groups: ['group1', 'group2',...], users: ['user1','user2',...], } You could now query for all documents visible to user X if you have a list of groups user X belongs to by querying: db.documents.find( { $or : [ { public : true }, { users : X }, { groups : { $in : [list-of-X's-groups] } } ] } )

Otherwise, if the number of books per publisher is unbounded, this data model would lead to mutable, growing arrays, as in the following example:

One pretty easy way to include some “built-in” database documentation for your databases (which could be the beginnings of a data dictionary) is to add extended properties on your objects.

Microsoft Compiled HTML Help is a Microsoft proprietary online help format, consisting of a collection of HTML pages, an index and other navigation tools. The files are compressed and deployed in a binary format with the extension .CHM, for Compiled HTML. The format is often used for software documentation.

There is however Morphia, an Object Document Mapper for MongoDB + Java which closely emulates the JPA model but using MongoDB appropriate semantics

DataNucleus already supports MongoDB, for JPA and JDO, the standardised APIs in Java.

clipseLink is planning support for MongoDB from JPA.

Supports Google account and OpenID authentication and access control on each JSON document. Provides admin console for setting the access control.

Python Tools for Visual Studio includes support for discovering, executing and debugging unit tests. This allows you to author your tests and run them without having to switch to a command prompt.

Class and module level fixtures are implemented in TestSuite