As we know we can build great application with django using postgresql database or additional scalability and feature, sometime we use redis
I have notice some people using mongodb in their django project. My question is, what is the case and what specific purpose they are using mongoDB in their django project.
Why can't those feature can't be achieved by postgresql or redis?
mongoDB and redis are Non-Relational (No-SQL) Databases.
postgresql is a Relational (SQL) Database.
Choosing the type of DB depends on people's requirements.
SQL Databases
SQL databases are known as relational databases, and have a table-based data structure, with a strict, predefined schema required.
Eg: Oracle, MySQL, Microsoft SQL Server, and PostgreSQL
No-SQL Databases
NoSQL databases, or non-relational databases, can be document based, graph databases, key-value pairs, or wide-column stores. NoSQL databases don’t require any predefined schema, allowing you to work more freely with “unstructured data.”
Examples:
Document: MongoDB and CouchDB
Key-value: Redis and DynamoDB
Wide-column: Cassandra and HBase
Graph: Neo4j and Amazon Neptune.
What is the case and what specific purpose they are using mongoDB in their django project?
There are many reasons for that.
I suggest you to read this to know why and in what cases people choose No-SQL DBs over Relational DBs - No-SQL vs Relational DBs
Related
I have a working Django web application that currently uses Postgresql as the database. Moving forward I would like to perform some analytics on the data and also generate reports etc. I would like to make use of Amazon Redshift as the data warehouse for the above goals.
In order to not affect the performance of the existing django web application, I was thinking of writing a NEW Django application that essentially would leverage a READ-ONLY replica of the Postgresql database and continuously write data from read-only replicas to the Amazon Redshift. My thinking is that perhaps the NEW Django application can be used to handle some/all of the Extract, Transform and Load functions
My questions are as follows:
1. Does the Django ORM work well with Amazon Redshift? If yes, how does one handle the model schema translations? Any pointers in this regard would be greatly appreciated.
2. Is there any better alternative to achieve the goals listed above?
Thanks in advance.
This is more of an architectural question than a technological one per se.
I am currently building a business website/social network that needs to store large volumes of data and use that data to draw analytics (consumer behavior).
I am using Django and a PostgreSQL database.
Now my question is: I want to expand this architecture to include a data warehouse. The ideal would be: the operational DB would be the current Django PostgreSQL database, and the data warehouse would be something additional, preferably in a multidimensional model.
We are still in a very early phase, we are going to test with 50 users, so something primitive such as a one-column table for starters would be enough.
I would like to know if somebody has experience in this situation, and that could recommend me a framework to create a data warehouse, all while mantaining the operational DB with the Django models for ease of use (if possible).
Thank you in advance!
Here are some cool Open Source tools I used recently:
Kettle - great ETL tool, you can use this to extract the data from your operational database into your warehouse. Supports any database with a JDBC driver and makes it very easy to build e.g. a star schema.
Saiku - nice Web 2.0 frontend built on Pentaho Mondrian (MDX implementation). This allows your users to easily build complex aggregation queries (think Pivot table in Excel), and the Mondrian layer provides caching etc. to make things go fast. Try the demo here.
My answer does not necessarily apply to data warehousing. In your case I see the possibility to implement a NoSQL database solution alongside an OLTP relational storage, which in this case is PostgreSQL.
Why consider NoSQL? In addition to the obvious scalability benefits, NoSQL offer a number of advantages that probably will apply to your scenario. For instance, the flexibility of having records with different sets of fields, and key-based access.
Since you're still in "trial" stage you might find it easier to decide for a NoSQL database solution depending on your hosting provider. For instance AWS have SimpleDB, Google App Engine provide their own DataStore, etc. However there are plenty of other NoSQL solutions you can go for that have nice Python bindings.
i'm new to the nosql world, and from forums and articles that i've read: most of users try to "mix" nosql tools, for example, they use Cassandra and MongoDB together to make a "powerful system", because am beginning with MongoDB, i've downloaded the DjanMon project (am a django fan ^_^ ), of course i've downloaded the special version of django that accepts the NoSql use: Django NonRel, and i've noticed that the Setting file dont "oblige" you to use one specific NoSql solution like in Django with RDBMS where you must specify MySql or PostegreSql or other solution, so, is it possible to mix lot of (or two of course) NoSql solution using Django (for example MongoDB+Cassandra)?
There's nothing to stop you using multiple storage solutions, whether SQL or NoSQL - but the NoSQL solutions all have different architectures, data models and APIs (For example, MongoDB is a document-oriented database, whereas Cassandra is Column-oriented), so you can't usually swap one for another without some effort.
Can you clarify what you are actually trying to achieve? I.e. why are you interested in mixing these two specific solutions?
Django (http://djangoproject.com) framework currently supports the following databases: PostgreSQL, SQLite 3, MySQL 5 and Oracle. This question is not about the comparison of these databases, contrariwise I want to know details about their compatibility with Django and how one should choose an adequate database for a simple (but growing) project.
It depends. If you don't want to pay the (huge) premium for Oracle, your choice is between MySQL and PostgreSQL (SQLite is mostly meant for development, not production). PostgreSQL seems to be the choice of most Django core devs (Andrew Godwin went as far as putting "friends don't let friends use MySQL" into a DjangoCon talk). Nevertheless, MySQL is fully supported by Django and is used by many Django websites in production.
IMHO, PostgreSQL has two clear advantages over MySQL:
If you use GeoDjango. There's really no alternative to PostGIS. MySQL's GIS support is lackluster at best.
South. MySQL is not able to use transactions during schema migrations, which means if a South migration goes awry, you're hanging between two migrations without clear way forward or backward. PostgreSQL saves a lot of pain in such situations.
The quick answer is it doesn't really matter but if I had to pick one, it would probably be PostgreSQL.
The original Django developers heavily recommended PostgreSQL in the early days. PostgreSQL is arguably/technically a 'better' database then MySQL so if you've never used it before it might be worth investing some time to lean it.
Now-a-days though I'd say it's safe to assume that all the DB drivers work equally well. So if you are more familiar with MySQL or Oracle there should be no problems using them instead. I've only used Django with MySQL and haven't had any problems.
All of the pluggable databases are supported, meaning, the the model/db-layer will abstract the db-specifics for you. As for performance, I'd suggest MySQL 5 or Postgresql. Oracle will definitely perform well, but might be more expensive in the long run. If you are just started your project, sqlite3 is your friend, simply because the it will be setup within seconds.
Handling parallel settings for development and production has been discussed in various blog posts, e.g. in this one:
http://ericholscher.com/blog/2011/jan/10/handling-django-settings-files/
I am trying to understand how Django and Appengine work together?
First, question: Is this a good team?
Experience, what is possible and what not, would be great.
I also read some modules like auth, admin wont work.
But the article is rather old, so maybe there is an update.
And in that tutorial one has to import bforms.
What is that?
Django Module? Appengine? Python? Bigtable?
How is Bigtable different from regular SQL, MySQL?
Thanks
Regular SQL and MySQL are designed for one computer only and fail in cloud computing where you need 1,000 computers for one database. Thus the next generation databases, like bigtable, were created to distribute the data over many database servers. They are called NoSQL databases for "Not Only SQL." See http://nosql-database.org/ for a list of NoSQL databases. The google app engine apparently allows you to use the bigtable structure so you data is distributed over a dozen database servers in the cloud. So does Amazon's simple db.