document-database

Here is a document in the store: { "Name": "Hibernating Rhinos", "Employees": [ { "Name": "Ayende" }, { "Name": "John" }, { "Name": "Bob" }, { "Name": "Tom" }, { "Name": "Lane" }, { "Name": "Bill" }, { "Name": "Tad" } ] } It is easy to load this document with or without Employees collection, but how to load only part of inner collection? For instance, first 5 items: { "Name": "Hibernating Rhinos", "Employees": [ { "Name": "Ayende" }, { "Name": "John" }, { "Name": "Bob" }, { "Name": "Tom" }, { "Name": "Lane" } ] } Ayende Rahien Not directly, not. What you can do is define the following index:

I'm learning about data modeling in DocumentDb. Here's where I need some advice Please see what my documents look like down below. I can take two approaches here both with pros and cons. Scenario 1: If I keep the data denormalized (see my documents below) by keeping project team member information i.e. first, last name, email, etc. in the same document as the project, I can get the information I need in one query BUT when Jane Doe gets married and her last name changes, I'd have to update a lot of documents in the Projects collection. I'd also have to be extremely careful in making sure that

I am developing a web-based application using Rails. I am debating between using a Graph Database, such as InfoGrid, or a Document Database, such as MongoDB. My application will need to store both small sets of data, such as a URL, and very large sets of data, such as Virtual Machines. This data will be tied to a single user. I am interested in learning about peoples experiences with either Graph or Document databases and why they would use either of the options. Thank you I don't feel enough experienced with both worlds to properly and fully answer your question, however I'm using a document

I was able to successfully run a simple test for RavenDB based on the code found at: http://ravendb.net/tutorials/hello-world Next I tried to run it in an Embedded Manner, but I keep on getting the following error: Message: Could not find transactional storage type: Raven.Storage.Esent.TransactionalStorage, Raven.Storage.Esent StackTrace: at Raven.Database.Config.InMemoryRavenConfiguration.CreateTransactionalStorage(Action notifyAboutWork) in c:\Builds\raven\Raven.Database\Config\InMemoryRavenConfiguration.cs:line 272 at Raven.Database.DocumentDatabase..ctor(InMemoryRavenConfiguration

It seems to me that when you are creating a Mongo document and have a field {key, value} which is sometimes not going to have a value, you have two options: Write {key, null} i.e. write null value in the field Don't store the key in that document at all Both options are easily queryable, in one you query for {key : null} and the other you query for {key : {$exists : false}} . I can't really think of any differences between the two options that would have any impact in an application scenario (except that option 2 has slightly less storage). Can anyone tell me if there are any reasons one would

It seems like I run into lots of situations where the appropriate way to build my data is to split it into two documents. Let's say it was for a chain of stores and you were saving which stores each customer had visited. Stores and Customers need to be independent pieces of data because they interact with plenty of other things, but we do need to relate them. So the easy answer is to store the user's Id in the store document, or the store's Id in the user's document. Often times though, you want to access 1-2 other pieces of data for display purposes because Id's aren't useful. Like maybe the

For a small PHP app I am writing, we need to store a large number of records that have a hash key, and a few simple field values ('host', 'path'). eg: '4420ffb32a' => array( 'host' => '127.0.0.1', 'path' => 'path/to/resource', ); What is the best persistent storage for data like this? Would MySQL be the best choice, or is it overkill for such simple data? What would give the best performance? Short answer: Membase . Long answer: You basically have three options: a relational database, file storage, or something else. Like you said, a relational database could definitely be overkill. That said,