I have a companies collection that has three companies(at the moment). There is also a second collection called campaigns. Each campaign belongs to a company. Each campaign has different fields depending on what company it is. Because mongodb is schemaless does that mean that I can add whatever fields I want to the collection. Like if I created a template form for each company could I save whatever template was selected.
Short answer
Yes.
Longer answer
While MongoDB does not enforce a schema (save for the required _id field), it is good to have at least some schema to your documents. If you store extremely different documents in a single collection, it can make it very challenging to handle all the different document forms in your code. This usually makes development much harder.
Typically companies have common data associated with them, so you will still have a common schema between them. But each company can expand upon that base schema. Just be sure to appropriately handle all of the potential null values for fields in your code.
Ok so the more and more I develop in Mongodb i start to wonder about the need for multiple collections vs having one large collection with indexes (since columns and fields can be different for each document unlike tabular data). If i am trying to develop in the most efficient way possible (meaning less code and reusable code) then can I use one collection for all documents and just index on a field. By having all documents in one collection with indexes then i can reuse all my form processing code and other code since it will all be inserting into the same collection.
For Example:
Lets say i am developing a contact manager and I have two types of contacts "individuals" and "businesses". My original thought was to create a collection called individuals and a second collection called businesses. But that was because im used to developing in sql where yes this would be appropriate since columns would be different for each table. The more i started to think about the flexibility of document dbs the more I started to think, "do I really need two collections for this?" If i just add a field to each document called "contact type" and index on that, do i really need two collections? Since the fields/columns in each document do not have to be the same for all (like in sql) then each document can have their own fields as long as i have a "document type" field and an index on that field.
So then i took that concept and started to think, if i only need one collection for "individuals" and "businesses" then do i even need a separate collection for "Users" or "Contact History" or any other data. In theory couldn't i build the entire solution in once collection and just have a field in each document that specifield the "type" and index on it such as "Users", "Individual Contact", "Business Contacts", "Contact History", etc, and if it is a document related to another document i can index on the "parent key/foreign" Id field...
This would allow me to code the front end dynamically since the form processing code would all be the same (inserting into the same collection). This would save a lot of coding but i want to make sure by using indexes and secondary indexes that the db would still run fast and not cause future problems as the collection grew. As you can imagine, if everything was in one collection there might be hundreds of thousands even millions of documents in this collection as the user base grows but it would have indexes and secondary indexes to optimize performance.
My question is: Is this a common method mongodb developers use? Why or why not? What are the downfalls, if any? If this is a commonly used method, please also give any positives to using this method. thank you.
This is a really big point in Mongo and the answer is a little bit more of an art than science. Having one collection full of gigantic documents is definitely an anti-pattern because it works against many of Mongo's features.
For instance, when retrieving documents, you can only retrieve a whole document out of a collection (not entirely true, but mostly). So if you have huge documents, you're retrieving huge documents each time. Also, having huge documents makes sharding less flexible since only the top level documents are indexed (and hence, sharded) in each collection. You can index values deep into a document, but the index value is associated with the top level document.
At the same time, going purely relational is also an anti-pattern because you've lost a lot of the referential integrity by going to Mongo in the first place. Also, all joins are done in application memory, so each one requires a full round-trip (slow).
So the answer is to do something in between. I'm thinking you'll probably want a collection for individuals and a different collection for businesses in this case. I say this because it seem like businesses have enough meta-data associated that it could bulk up a lot. (Also, I individual-business relationship seems like a many-to-many). However, an individual might have a Name object (with first and last properties). That would be a bad idea to make Name into a separate collection.
Some info from 10gen about schema design: http://www.mongodb.org/display/DOCS/Schema+Design
EDIT
Also, Mongo has limited support for transactions - in the form of atomic aggregates. When you insert an object into mongo, the entire object is either inserted or not inserted. So you're application domain requires consistency between certain objects, you probably want to keep them in the same document/collection.
For example, consider an application that requires that a User always has a Name object (containing FirstName, LastName, and MiddleInitial). If a User was somehow inserted with no corresponding Name, the data would be considered to be corrupted. In an RDBMS you would wrap a transaction around the operations to insert User and Name. In Mongo, we make sure Name is in the same document (aggregate) as User to achieve the same effect.
Your example is a little less clear, since I don't understand the business cases. One thing that does come to mind is that Mongo has excellent support for inheritance. It might make sense to put all users, individuals, and potentially businesses into the same collection (depending on how the application is modeled). If one individual has many contacts, you probably want individuals to have an array of IDs. If your application requires that you get a quick preview of contacts, you might consider duplicating part of an individual and storing an array of contact objects.
If you're used to RDBMS thinking, you probably think all your data always has to be consistent. The truth is, that's probably not entirely true. This concept of applying atomic aggregates to the domain has been preached heavily by the DDD community recently. When you look at your domain in depth, like your business users do, the consistency boundaries should become distinct.
MongoDB, and NoSQL in general, is about de-normalising data and about reducing joins. It goes against normal SQL thinking.
In your case, I don't see any reason why you would want to have separate collections because it introduces unnecessary complexity and performance overhead. Consider, for example, if you wanted to have a screen that displayed all contacts, in alphabetical order. If you have one single collection for contacts, then its really easy, but if you have two collections it becomes a more complicated proposition.
Where I would have multiple collections is if your application had multiple users storing contacts. I would then have one collection for each user. This makes it so easy to extract out that users contacts.
I have 1 collection called Visit, in it I save documents with information about visit referrer, page, keyword, dates, so on.
I think Keyword can be considered a collection on it's own, the same for Page.
This will force me to create different collections but I'm not sure if this is the right way to go.
In a traditional DB model, they will clearly be stored in separate tables connected with FK.
But what about mongo ?
Is it a good practice for keys to have the same value over and over again for different documents and just create a collection in this case ?
One of the benefits of MongoDB is its ability to embed documents.
It is perfectly reasonable for the documents in your Visits collection to contain Keyword and Page Sub-Documents.
The rule of thumb is embed documents for speed, normalize documents for consistency.
If you embed the Keyword and Page documents in your Visit document, your application will only have to make one query to retrieve all of the relevant information. (speed)
However, the drawback is that if the Keyword and/or Page information is updated, it will have to be updated in every other Visit document where it appears. If many different Visit documents will rely on the same Keyword and Page documents, it may be better to keep them in a separate collection, especially if they will be changed frequently. (consistency)
This is of course a generalization, and ultimately it is up to you, the application developer to decide which works best for your unique situation. There is additional information on Embedding versus Linking in the Mongo Document titled "Schema Design"
http://www.mongodb.org/display/DOCS/Schema+Design
You may also find the article "MongoDB Data Modeling and Rails" to be beneficial:
http://www.mongodb.org/display/DOCS/MongoDB+Data+Modeling+and+Rails
The example is given in Rails, but the theory on Document design applies to any language.
Good luck!
I'm pretty new to MongoDB and NoSQL in general. I have a collection Topics, where each topics can have many comments. Each comment will have metadata and whatnot making a Comments collection useful.
In MySQL I would use foreign keys to link to the Comments table, but in NoSQL should I just include the a Comments collection within the Topics collection or have it be in a separate collection and link by ids?
Thanks!
Matt
It depends.
It depends on how many of each of these type of objects you expect to have. Can you fit them all into a single MongoDB document for a given Topic? Probably not.
It depends on the relationships - do you have one-to-many or many-to-many relationships? If it's one-to-many and the number of related entities is small you might chose to put embed them in an IList on a document. If it's many-to-many you might chose to use a more traditional relationship or you might chose to embed both sides as ILists.
You can still model relationships in MongoDB with separate collections BUT there are no joins in the database so you have to do that in code. Loading a Topic and then loading the Comments for it might be just fine from a performance perspective.
Other tips:
With MongoDB you can index INTO arrays on documents. So don't think of an Index as just being an index on a simple field on a document (like SQL). You can use, say, a Tag collection on a Topic and index into the tags. (See http://www.mongodb.org/display/DOCS/Indexes#Indexes-Arrays)
When you retrieve or write data you can do a partial read and a partial write of any document. (see http://www.mongodb.org/display/DOCS/Retrieving+a+Subset+of+Fields)
And, finally, when you can't see how to get what you want using collections and indexes, you might be able to achieve it using map reduce. For example, to find all the tags currently in use sorted by their frequency of use you would map each Topic emitting the tags used in it, and then you would reduce that set to get the result you want. You might then store the result of that map reduce permanently and only up date it when you need to.
It's a fairly significant mind-shift from relational thinking but it's worth it if you need the scalability and flexibility a NOSQL approach brings.
Also look at the Schema Design docs (http://www.mongodb.org/display/DOCS/Schema+Design). There are also some videos/slides of several 10Gen presentations on schema design linked on the Mongo site. See http://www.mongodb.org/pages/viewpage.action?pageId=17137769 for an overview.
I'm interested in document-oriented databases, and I'd like to play with MongoDB. So I started a fairly simple project (an issue tracker), but am having hard times thinking in a non-relational way.
My problems:
I have two objects that relate to each other (e.g. issue = {code:"asdf-11", title:"asdf", reporter:{username:"qwer", role:"manager"}} - here I have a user related to the issue). Should I create another document 'user' and reference it in 'issue' document by its id (like in relational databases), or should I leave all the user's data in the subdocument?
If I have objects (subdocuments) in a document, can I update them all in a single query?
I'm totally new to document-oriented databases, and right now I'm trying to develop sort of a CMS using node.js and mongodb so I'm facing the same problems as you.
By trial and error I found this rule of thumb: I make a collection for every entity that may be a "subject" for my queries, while embedding the rest inside other objects.
For example, comments in a blog entry can be embedded, because usually they're bound to the entry itself and I can't think about a useful query made globally on all comments. On the other side, tags attached to a post might deserve their own collection, because even if they're bound to the post, you might want to reason globally about all the tags (for example making a list of trending topics).
In my mind this is actually pretty simple. Embedded documents can only be accessed via their master document. If you can envision a need to query an object outside the context of the master document, then don't embed it. Use a ref.
For your example
issue = {code:"asdf-11", title:"asdf", reporter:{username:"qwer", role:"manager"}}
I would make issue and reporter each their own document, and reference the reporter in the issue. You could also reference a list of issues in reporter. This way you won't duplicate reporters in issues, you can query them each separately, you can query reporter by issue, and you can query issues by reporter. If you embed reporter in issue, you can only query the one way, reporter by issue.
If you embed documents, you can update them all in a single query, but you have to repeat the update in each master document. This is another good reason to use reference documents.
The beauty of mongodb and other "NoSQL" product is that there isn't any schema to design. I use MongoDB and I love it, not having to write SQL queries and awful JOIN queries! So to answer your two questions.
1 - If you create multiple documents, you'll need make two calls to the DB. Not saying it's a bad thing but if you can throw everything into one document, why not? I recall when I used to use MySQL, I would create a "blog" table and a "comments" table. Now, I append the comments to the record in the same collection (aka table) and keep building on it.
2 - Yes ...
The schema design in Document-oriented DBs can seems difficult at first, but building my startup with Symfony2 and MongoDB I've found that the 80% of the time is just like with a relational DB.
At first, think it like a normal db:
To start, just create your schema as you would with a relational Db:
Each Entity should have his own Collection, especially if you'll need to paginate the documents in it.
(in Mongo you can somewhat paginate nested document arrays, but the capabilities are limited)
Then just remove overly complicated normalization:
do I need a separate category table? (simply write the category in a column/property as a string or embedded doc)
Can I store comments count directly as an Int in the Author collection? (then update the count with an event, for example in Doctrine ODM)
Embedded documents:
Use embedded documents only for:
clearness (nested documents like: addressInfo, billingInfo in the User collection)
to store tags/categories ( eg: [ name: "Sport", parent: "Hobby", page: "/sport"
] )
to store simple multiple values (for eg. in User collection: list of specialties, list of personal websites)
Don't use them when:
the parent Document will grow too large
when you need to paginate them
when you feel the entity is important enough to deserve his own collection
Duplicate values across collection and precompute counts:
Duplicate some columns/attributes values from a Collection to another if you need to do a query with each values in the where conditions. (remember there aren't joins)
eg: In the Ticket collection put also the author name (not only the ID)
Also if you need a counter (number of tickets opened by user, by category, ecc), precompute them.
Embed references:
When you have a One-to-Many or Many-to-Many reference, use an embedded array with the list of the referenced document ids (see MongoDB DB Ref).
You'll need to use an Event again to remove an id if the referenced document get deleted.
(There is an extension for Doctrine ODM if you use it: Reference Integrity)
This kind of references are directly managed by Doctrine ODM: Reference Many
Its easy to fix errors:
If you find late that you have made a mistake in the schema design, its quite simply to fix it with few lines of Javascript to run directly in the Mongo console.
(stored procedures made easy: no need of complex migration scripts)
Waring: don't use Doctrine ODM Migrations, you'll regret that later.
Redid this answer since the original answer took the relation the wrong way round due to reading incorrectly.
issue = {code:"asdf-11", title:"asdf", reporter:{username:"qwer", role:"manager"}}
As to whether embedding some important information about the user (creator) of the ticket is a wise decision or not depends upon the system specifics.
Are you giving these users the ability to login and report issues they find? If so then it is likely you might want to factor that relation off to a user collection.
On the other hand, if that is not the case then you could easily get away with this schema. The one problem I see here is if you wish to contact the reporter and their job role has changed, that's somewhat awkward; however, that is a real world dilemma, not one for the database.
Since the subdocument represents a single one-to-one relation to a reporter you also should not suffer fragmentation problems mentioned in my original answer.
There is one glaring problem with this schema and that is duplication of changing repeating data (Normalised Form stuff).
Let's take an example. Imagine you hit the real world dilemma I spoke about earlier and a user called Nigel wants his role to reflect his new job position from now on. This means you have to update all rows where Nigel is the reporter and change his role to that new position. This can be a lengthy and resource consuming query for MongoDB.
To contradict myself again, if you were to only have maybe 100 tickets (aka something manageable) per user then the update operation would likely not be too bad and would, in fact, by manageable for the database quite easily; plus due to the lack of movement (hopefully) of the documents this would be a completely in place update.
So whether this should be embedded or not depends heavily upn your querying and documents etc, however, I would say this schema isn't a good idea; specifically due to the duplication of changing data across many root documents. Technically, yes, you could get away with it but I would not try.
I would instead split the two out.
If I have objects (subdocuments) in a document, can I update them all in a single query?
Just like the relation style in my original answer, yes and easily.
For example, let's update the role of Nigel to MD (as hinted earlier) and change the ticket status to completed:
db.tickets.update({'reporter.username':'Nigel'},{$set:{'reporter.role':'MD', status: 'completed'}})
So a single document schema does make CRUD easier in this case.
One thing to note, stemming from your English, you cannot use the positional operator to update all subdocuments under a root document. Instead it will update only the first found.
Again hopefully that makes sense and I haven't left anything out. HTH
Original Answer
here I have a user related to the issue). Should I create another document 'user' and reference it in 'issue' document by its id (like in relational databases), or should I leave all the user's data in the subdocument?
This is a considerable question and requires some background knowledge before continuing.
First thing to consider is the size of a issue:
issue = {code:"asdf-11", title:"asdf", reporter:{username:"qwer", role:"manager"}}
Is not very big, and since you no longer need the reporter information (that would be on the root document) it could be smaller, however, issues are never that simple. If you take a look at the MongoDB JIRA for example: https://jira.mongodb.org/browse/SERVER-9548 (as a random page that proves my point) the contents of a "ticket" can actually be quite considerable.
The only way you would gain a true benefit from embedding the tickets would be if you could store ALL user information in a single 16 MB block of contigious sotrage which is the maximum size of a BSON document (as imposed by the mongod currently).
I don't think you would be able to store all tickets under a single user.
Even if you was to shrink the ticket to, maybe, a code, title and a description you could still suffer from the "swiss cheese" problem caused by regular updates and changes to documents in MongoDB, as ever this: http://www.10gen.com/presentations/storage-engine-internals is a good reference for what I mean.
You would typically witness this problem as users add multiple tickets to their root user document. The tickets themselves will change as well but maybe not in a drastic or frequent manner.
You can, of course, remedy this problem a bit by using power of 2 sizes allocation: http://docs.mongodb.org/manual/reference/command/collMod/#usePowerOf2Sizes which will do exactly what it says on the tin.
Ok, hypothetically, if you were to only have code and title then yes, you could store the tickets as subdocuments in the root user without too many problems, however, this is something that comes down to specifics that the bounty assignee has not mentioned.
If I have objects (subdocuments) in a document, can I update them all in a single query?
Yes, quite easily. This is one thing that becomes easier with embedding. You could use a query like:
db.users.update({user_id:uid,'tickets.code':'asdf-1'}, {$set:{'tickets.$.title':'Oh NOES'}})
However, to note, you can only update ONE subdocument at a time using the positional operator. As such this means you cannot, in a single atomic operation, update all ticket dates on a single user to 5 days in the future.
As for adding a new ticket, that is quite simple:
db.users.update({user_id:uid},{$push:{tickets:{code:asdf-1,title:"Whoop"}}})
So yes, you can quite simply, depending on your queries, update the entire users data in a single call.
That was quite a long answer so hopefully I haven't missed anything out, hope it helps.
I like MongoDB, but I have to say that I will use it a lot more soberly in my next project.
Specifically, I have not had as much luck with the Embedded Document facility as people promise.
Embedded Document seems to be useful for Composition (see UML Composition), but not for aggregation. Leaf nodes are great, anything in the middle of your object graph should not be an embedded document. It will make searching and validating your data more of a struggle than you'd want.
One thing that is absolutely better in MongoDB is your many-to-X relationships. You can do a many-to-many with only two tables, and it's possible to represent a many-to-one relationship on either table. That is, you can either put 1 key in N rows, or N keys in 1 row, or both. Notably, queries to accomplish set operations (intersection, union, disjoint set, etc) are actually comprehensible by your coworkers. I have never been satisfied with these queries in SQL. I often have to settle for "two other people will understand this".
If you've ever had your data get really big, you know that inserts and updates can be constrained by how much the indexes cost. You need fewer indexes in MongoDB; an index on A-B-C can be used to query for A, A & B, or A & B & C (but not B, C, B & C or A & C). Plus the ability to invert a relationship lets you move some indexes to secondary tables. My data hasn't gotten big enough to try, but I'm hoping that will help.