In this git, you will find examples on how IRIS can be an fast an flexible database.
IRIS can be seen as an multidimensional database what does that mean ?
Here is some dimension, this is not exautif.
In this demo we will be play with few of thoses dimentions.
To run this demo, you just need to clone this git :
git clone https://github.com/grongierisc/iris-devslam.gitThen run the docker-compose file :
docker-compose up -dThen you will able to access all the notebook below.
In this first demo we will learn the diffrance between row storage and column storage.
Then we will generate 1 billion of rows in less than 3 minutes.
Those data will help us to understand the benefit of column storage.
on-prems :
http://127.0.0.1:8888/notebooks/row_column/demo.ipynb
source file :
In this second demo we will compare the performance of IRIS vs Redis.
Redis is an in-memory database, IRIS can alse act as an in-memory database with option to persist data on disk.
Will this option make IRIS slower ?
on-prems :
http://127.0.0.1:8888/notebooks/bench_redis_iris/demo.ipynb
source file :
Just after reaching the speed of light, we will see how IRIS can be used as an SQL database and as an NoSQL database at the same time.
on-prems :
http://127.0.0.1:8888/notebooks/multi_model/demo.ipynb
source file :
This is the IRIS Framework.
The components inside of IRIS represent a production. Inbound adapters and outbound adapters enable us to use different kind of format as input and output for our database.
The composite applications will give us access to the production through external applications like REST services.
The arrows between them all of this components are messages. They can be requests or responses.
And finally we will talk about the python framework.
This framework help you to organize you python code in a way that is easy to understand and easy to maintain.