I'm fixing the usability/documentation for the mean stack. I'm starting with Mean.JS. Can someone give me the salient reasons why the authors of the MEAN stack use MongoDB as the database? There are other databases to choose, but MongoDB is used for some reason.
I realize there are questions already covering databases, but I'm wondering specifically why it was used in the MEAN stack scenario.
It think the primary reason is that MongoDB uses the same language Javascript (ECMA Script) for methods and functions API, rather than a separate language (like SQL). Thus MongoDB is a good no SQL database option, and it works much more efficiently as a database for the rest of the stack.
As others have pointed out, there are many other reasons, like that it is the most popular NoSQL database at this point. It has a decent shell and you can write Javascript in it. It is Open Source and well documented.
It is also really easy to setup, and scales fairly well, although not as good as some other NoSQL databases.
It also uses BSON, which is similar to JSON, which is similar to a Javascript object. So it is just plain easy to learn and easy to use this particular database with the rest of a Javascript stack.
There's some pretty good reasons here: http://blog.mongodb.org/post/49262866911/the-mean-stack-mongodb-expressjs-angularjs-and
A Glimpse Into Four Key Components - How MEAN Stack Adds New Dimensions To New-Age Web Applications
All four components of MEAN Stack are popular in the app development space. It offers a platform that enables an effortless development work process. Let’s know about every component and its unique features.
MongoDB – Independent database framework
For any web app building, data storage and management are essential. MongoDB is a popular database with NoSQL document to allow this purpose. The primary use case of this framework is to enable data storage and management of every web application development.(Read More)
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I was reading at this article https://www.infoq.com/articles/spring-data-intro to understand how can a data service layer be independent of database(RDBMS /NoSQL). It looks like there's no way to design entity and repository to be independent of database. This article was written on 2012. Do we've any other technologies since then that has implemented this feature?
Before actually answering your question I have to ask: Why do you want to do that? Think twice because abstraction comes at a cost and just doing it in order to have a "clean" design is most certainly not worth it.
Now to your question:
There is no library or framework that does this out of the box.
Probably the thing getting closest to it is spring data which you are obviously aware of. If you stick to the persistent storage independent interfaces your repositories will abstract over the persistence store use at least to some extent. BUT: you will have to provide different kinds of metadata (typically as annotations on the entities) to make it work. So in this sense, it is a really leaky abstraction.
Of course, you can roll your own: create an interface with the operations you need and provide implementations for the different data stores you want to use. Also, include a storage independent way of providing metadata.
So the question becomes: Why hasn't anybody done that yet? And why you probably shouldn't do it either?
It is hard: Just writing SQL in a way that all (relevant) SQL databases understand is difficult, see this for an example.
You loose a lot of power of your stores. For example, RDBMSes are great at joining stuff. But joining is basically a no go for many No-SQL databases. So your API probably shouldn't offer this feature. This basically dumbs everything down to the common denominator, which is going to be really small when you have very different data stores.
It is not worth it. This leads back to my opening question: Why would you want to do it anyway? I certainly see the use of switching different RDBMSes. Some companies only want certain vendors in their datacenter, it is nice to have an in memory variant for testing and so on. But switching a store from for example Oracle to Hazelcast and then to MongoDB to CSV? Why would you want to do that? What is the business value of that?
I'm currently planning a social-media application - especially the backend.
Basically I have all the social aspects for which I want to use SQL (PostgreSQL I guess) but I also have geolocations organized in lists (so many-to-one) which will propably make out the biggest ammount of data. I know that PostgreSQL has modules for GIS capabilities and my initial thought was to just use PostgreSQL for everything, just for the sake of simplicity and because performance of Geolocation searches should be around the same for both systems, if not even in favor of PostgreSQL. I can also use JSON Type in PostgreSQL so it basically has the most obvious advantages of MongoDB covered.
On the other hand I'm affraid of scalability as the geolocations are going to be the biggest chunk of data and the tables are propably going have heaps of rows.
So my thought now is to implement geolocations in MongoDB with its easy scalability, easy to use geolocation search and embedd e.g Comments/Likes for a geolocation directly into the document, which would make the geolocation reads/searches way easier but then again I had to combine this data with social data from SQL, e.g fetch all users that commented a geolocation and get their profile info from PostgreSQL and 'manually' combine it. Even though parts of this could be done on frontend saving me a lot of resources.
I'm not sure how good this idea performs and if I'm really doing myself a favor there.
tldr: Use PostgreSQL.
Long answer:
You are trying to pre-optimize for a problem you don't even know if you will have. You don't know how many geolocations you will have, what the usage behaviors will be of your users and you probably don't even have any users yet.
I've used MongoDB before and migrated to PostgreSQL. There are many, many features and benefits to using a 'real' database for storing highly structured data. I suggest googling around for 'PostgreSQL vs X' articles, but the overall consensus that I've found is that PGSQL is extremely mature, reliable, performant and supported.
From my personal experience using Mongo then switching to PGSQL, I will never use Mongo again unless PGSQL (or another full-fledged SQL database) is completely falling over and I've spent months fixing it. Even then I'd take a hard look at other NoSQL databases too. PGSQL has so many amazing features and powerful tools that make it a joy to use.
For the seemingly few things you think you need Mongo for, PGSQL can do, and do just as well or better. It has native JSON types with indexes, geo support, full text indexing, etc. PGSQL has been around longer and has more support (useful for debugging, performance tuning, etc).
Regardless of which technologies you are thinking of using, you can't make any sort of informed decision if you don't:
Test with large data sets
and
Know your usage patterns and data volumes
So at this point I'd pick the more matured and powerful tool and setup monitoring for it. Watch the usage and performance of PGSQL, see how it holds up. Research best practices for PGSQL. Get to know it, learn it, dive in deep. When it comes to scaling individual services, each one is somewhat unique and will not fit a simple "Should I use X or Y?" question.
Good luck!
I'm developing a brand new project in Scala. It's just an application for a bunch of CRUD operations, however, because of some eccentric requirements, Play2 or Lift does not fit the bill, so I'm going to develop the application from the ground up. This means that Anorm or ScalaQuery becomes less obvious choices for database integration, and leaves me with the question: is it time to try something new?
My past technology stacks mostly included Java and PostgreSQL and I have experience with both ORM and plain SQL. Are NoSQL database management systems like MongoDB a good replacement for a typical RDBMS or are they special case application data stores? Also, how does the choice of database effect the greater Scala system design (if at all)? For example, the fact that you are using a JSON-like interface to talk to the database, and JSON between the web and a REST service, does not mean that much if everything in the middle becomes Scala objects, or does it?
I'm basically asking for someone's experience on moving from relational to object/document type databases, using Scala in particular. I know that good RDBMS integration is promised in the upcoming release of SLICK. So, if a company like TypeSafe decides to make a RDBMS integration part of the TypeSafe stack, then will I be swimming upstream by integrating to MongoDB using Casbah for example?
Apologies if this question appears a bit vague. I do hope that someone with the right insights or experience will be able to help though.
Update:
Apologies for not adding links to SLICK (it being fairly new). Here goes:
Quick overview
Project home
Update 2:
My personal first win for a technology is usually developer productivity - this translates to lightweight and simple: quick to learn, easy to maintain, no magic
I am currently in a similar situation, and since I have some experience with web development and SQL databases, I took it as an opportunity to work with MongoDB, Cashbah (and Scalatra). My experience is still very limited and the project and the amount of data I am working with is pretty small, but here are a few observations I've made.
For the few sets of data I have, performance does not seem to motivate either SQL or NoSQL. However, performance in the presence of huge amounts of data is often listed as a reason for using NoSQL, e.g., by Wikipedia
My documents (entries in the database) arise from benchmarking test suits, and mainly have a static structure, and I am optimistic that I could store them in a fixed-schema SQL database. However, a few substructures are not static, e.g., new test cases are added, new statistics are tracked, others are removed. This was my main motivation for trying a schema-free NoSQL database. Also, because I had the feeling that the document approach of MongoDB makes it much more obvious which data belongs together (i.e., to a document), in contrast to entries in a relational database, where the data would be distributed over various tables and rows, and where a full "document" would need to be reconstructed by joins.
Tools such as Lift-Json or Rogue allow you to work with regular Scala objects in a type-safe, although the data is regularly (de-)serialised as (from) JSON. However, this naturally works best if the structure of your data is mainly static, otherwise, you you are left with using strings to access your data (e.g., for expanding the results of a query using Cashbah).
If you are mainly concerned about a coherent representation of data on server and client side, languages such as Opa or Haxe might be of interest, since they compile to code that can executed on both sides. See this page for "multitarget" or "tierless" languages.
Got too long for a comment. Was just trying to relate my short experience with Scala (about 6 months now, since about when Play2 came out--it's quickly become my go to language).
I've enjoyed using Salat/Casbah with MongoDB in my last few projects; most have been in Play2, but the latest was without a webapp framework. It definitely hasn't felt like swimming upstream.
I would say that there are particular use cases for which I wouldn't use mongo, but it works nicely as a general purpose object data store, especially if you expect to query by id or index and don't need transactions (and will need minimal ad-hoc aggregation type stuff).
Expect to require a separate set of servers dedicated to mongodb (or to use a service dedicated to mongodb), but I guess that's normal for most serious database apps.
I've also used Play2/Anorm, which was surprisingly enjoyable to use for some ad-hoc query dashboard-style report pages. I started trying to go the Squeryl route, but Anorm seemed easier to use for one-off aggregation queries. Haven't looked at SLICK, but it sounds interesting.
It's really hard to say without knowing what problems you would like the app to solve.
I've personally found my productivity increased using NoSQL DBs via REST/JSON. Though bear in mind most NoSQL DBs offer REST interfaces which preclude the need for much middleware, Scala or otherwise, unless you intend to write a webapp with a UI.
If this is a learning exercise, I recommend you try multiple things out, as each NoSQL DB has something different to offer to your toolkit, and have personally found CouchDB, Riak, Neo4j, and MongoDb all with various pluses and drawbacks and good for different purposes.
Hope this helps, good luck.
I was on my way for the Development of an Ecommerce app. Is it possible to write a lithium application that works on different connections basically MongoDb or CouchDb and MySQL? How can we do it and what are your tips on achieving it?
I'm not sure if I understand you right.
If you just want to use more connections at the same time to different databases, this is easily possible. You can just define more connections at once (take a look at the default connections.php bootstrap file and also at the documentation for the lithium\core\Environment class).
If you want to run your whole application on all the database mentioned above, read on...
It is not easy to answer this question in general, but here are some thoughts on this:
As you may know, Lithium provides you with a database abstraction layer which exposes general methods for the CRUD process. As nice this is during development (you don't have to learn new interfaces for every database), you soon come to a point where you need database specific features.
This may raise compatiblitiy problems between relational databases, but is nearly impossible for mixing relational and non-relational databases. Of course you can use them side-by-side, but providing abstractions is really hard. For example, how would you query on nested documents (like you do in MongoDB) in MySQL? You could write a wrapper that tries to emulate this, but you shouldnt try to.
That said, if you really have to do this, you may achieve it with writing wrapper code and leave out very specific database-dependend features.
I'm new to MongoDB, can anyone explain how it could be used in efficiently in enterprise applications, so as to give good performance (using joins, indexing etc.)
And perhaps also point me to any MongoDB production applications on the web.
For a good introduction to MongoDB, check out The Little MongoDB Book. Here's a list of sites currently using MongoDB in production.
You talk about Joins and Indexes. It seems your head is still in the RDBMS world. NoSQL and Mongo are not just different Relational Databases there a completely different way of managing and thinking of Data. You need to think of your data schema in terms of Structured Objects rather than rows.
Sounds like you need to start from the beginning. MongoDB.org has a lot of the info you're asking for already available. Specifically, read their page on use cases, and the page on production deployments.
A more specific question would receive more comprehensive answers and fewer downvotes.