Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 8 years ago.
Improve this question
I am going to start learning NOSQL databases (in practices, already done my researches and understood the concepts and modeling approaches).
I am working with time series data and both cassandra and mongodb are recommended for this use case.
I would like to know which one takes less time to learn? (Unfortunately, I don't have much time to spend on learning)
PS: I noticed that there are more tutorials and documentations with mongoDB (am I correct?)
Thank you!
Having used them both extensively, I can say that the learning curve isn't as bad as you might think. But as different people learn and absorb information at different rates, it is difficult to say which you will find easier or how quickly you will pick them up. I will mention that MongoDB has a reputation of being very developer-friendly, due to the fact that you can write code and store data without having to define a schema.
Cassandra has a little steeper learning curve (IMO). However that has been lessened due to the CQL table-based column families in recent versions, which help to bridge the understanding gap between Cassandra and a relational database. Since tutorials for MongoDB have been mentioned, I will post a link to DataStax's Academy, which offers a free online course you can take to introduce yourself to Cassandra. Specifically, the course DS220 deals with modeling your data.
With both, a key concept to understand is that you must break yourself of the relational database idea where you want to build your tables/collections to store your data most-efficiently. In non-relational data modeling you will want to model your tables/collections to reflect how you want to query your data, and this might mean using redundant data in some places.
qMongoFront is a qt based mongodb gui application under linux. It's free and opensouce. If you want to learn mongodb, qMongoFront is a good choice.
http://sourceforge.net/projects/qmongofront/
Related
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 1 year ago.
Improve this question
If there is any PLC programmer or Twincat3 user out there. I would like to write my master thesis on Twincat3 in a company. Basically, They have different kinds of the Test bench, and they want someone to develop drivers for them. I have no experience with PLC or C++ or IEC61131 languages. Is it possible to learn any of these in 3 months, and then start writing the thesis? I have three months of Internship time before starting. I am having a bit of doubt. Even though it is daunting as an Electrical engineering student, I have no other options.
I thank you in Advance.
Also, The test benches are mainly Powerelectronics or Electrical machine test bench. I believe I need to automate the test processes in twincat3.
Best Regards
Good choice with TwinCAT 3. TwinCAT 3 is very capable, and quite easy to learn (of course dependent on your background, but generally a good platform to work on).
All I can support you with is a link to a TwinCAT 3 tutorial that I've created that is free of charge (available on YouTube):
https://www.youtube.com/playlist?list=PLimaF0nZKYHz3I3kFP4myaAYjmYk1SowO
There are also some other resources available both on YouTube and on the website. I've created a set of links here to help you find all the resources you might need.
To answer your question I would say it depends. Three months is not much time, especially considering you probably have a lot of other things that need to go in there (doing studies, writing the thesis, implementation, conclusions etc). It depends on the complexity of your project (it's not very specific what "writing drivers for them" means). If it's a simple project (including a very basic set of I/Os) it might be do-able. If it's anything more complex (like needing to add a front-end, doing motion control and maybe even safety) then it's most likely going to be hard to finish it in three months.
But again, I think more details on what you want to achieve is necessary.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 8 years ago.
Improve this question
I already have a .Net Web project running on MongoDB where I store some news/feed data.
After a while I needed a faster way to track "who shared what" and "how to find relationships depending on these information".
Then I came up with an idea to use graphDB to track related feeds and users.
Since the system is already running on MongoDB, I am thinking of leaving the data in Mongo and creating the graph representation in Neo4J for applying a graph search.
I do not want to migrate all my data to Neo4J because many people telling me MongoDB's I/O performance is way better than Neo4J and they also pointed out Sharding feature.
What would you suggest in this situation?
And If I follow my idea, will it be a good practice?
Personnally I think there are no unique answer and best practices. It is common usage to use polyglot persistence systems.
Now everything is based on your context and there are points we can't just reply for you :
How much time do you have (learning a new technology is not a matter of days until you can use it in production and sleep good )
How much money you can invest in the project , sharding is, AFAIK, a neo4j enterprise feature and licenses have a cost if you're not opensource or commercial company. Also hosting costs for Neo4j in cluster mode.
How much data ? As long as your graph can fit in memory, you'll not run I/O issues.
Now, away from these points, yes you can in a first instance trying to map neo4j on top of mongoDB.
Maybe try to do incremental migrations, and at then end of the process, maybe ask you the following questions, WHY do you need MongoDB to handle graph structures ?
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 8 years ago.
Improve this question
I am sorry if this is not a constructive enough question.. Coming from the SQL world I'm just trying to wrap my head around this. After reading a lot about MongoDB, I've become very enthusiastic about it and consider using it for an upcoming application (in combination with Meteor).
However, I came across this blog post, which describes the troubles Diaspora ran into when using it and states "you should never use MongoDB". The examples she's giving sound pretty convincing.
Are these true problems with MongoDB, or were they using it wrong? Is this article now outdated and are there better ways for doing what they're doing (duplicate data for instance, like users being linked to each other, to posts and to comments, is a very common use case)?
Yes, there is a plenty of cases when mongodb not feet good, some of them are
When data perfectly described with 'table' metaphor (better using
SQL)
When you need ACID and transactions out of the box
When your workflow extremely oriented to write operation
When you need to generate complex cross-data reports
Data model have strongly relational view (a lot of connected
instances)
There is a lot of others, but this is just something which comes to my head fast.
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 5 years ago.
Improve this question
There are several MongoDB modules available for Node.js in the following link -
https://github.com/joyent/node/wiki/modules#wiki-db-nosql-mongo
Please, suggest me one (I'd like to know why you choose that one?).
It depends on what level of abstraction you want from your data. If you want something similar to an ORM, then Mongoose is the obvious choice and is popular.
However, the node-mongodb-native driver gives you clean duplication of almost the entire MongoDB API and since BSON is translated to JSON and JavaScript is a flexible dynamic language, there's really no need for an ORM. The latter does have benefits such a defining a schema which helps with validation and other tasks, but it also limits your flexibility.
Mongoskin is built atop node-mongodb-native but gives you the ability to have additional JavaScript method bindings and deal with connections and cursors easier. It's pretty lightweight, so you can stick with the basics or do more. This library is my personal preference and our team has built our own tooling and validation system around it.
Mongoose is a popular choice. But the documentation is just as bad (if not worse) than the MongoDB docs.
I personally prefer Mongolian, it's the closest thing you get to the Mongo shell and it's straight forward to use.
My fork adds very simple collection initialization.
Mongoose doesn't support bulk insert and it is schema-based. When you try to create different schemas for same collection, it throws exception. Consider carefully its suitability to your case before start with it.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 8 years ago.
Improve this question
I am trying to learn NoSQL, and am implementing that in a project I am working on now as a means to pick it up. I understand there are no hard rules around it. But I'd be happy to read on some of the following:
Guidelines on how to structure a NoSQL document.
Moving from a RDBMS to a NoSQL thinking.
Difference between storing data in a NoSQL to that from RDBMS
Thanks!
I do have previous experience in RDBMS, and have been working with them for years.
Every concept will require to learn new thinking. Your question is to general for a specific
answer.
You will structure and work with CouchDB documents in another way as with MongoDB documents. In CouchDB you will do queries with MapReduce. In MongoDB you have a flexible query interface similar to a RDBMS.
A Key-Value store requires a completely new way of thinking. You have to know your query patterns before you are able to structure your content the right way. You have no index, so you have to build your own structure.
One blog that gives a lot of NoSql information is http://nosql.mypopescu.com
Update
The Riak people have some interresting questions too:
Will my access pattern be read-heavy, write-heavy, or balanced?
Which datasets churn the most? Which ones require more sophisticated conflict resolution?
How will I find this particular type of data? Which method is most efficient?
How independent/interrelated is this type of data with this other type of data? Do they belong together?
How much will I need to do online queries on this data? How quickly do I need them to return results?