This seems to come up a lot in discussions so I wanted to provide my view on the differences. Imperative is focused on the steps required to meet an outcome. Declarative is focused on defining the end state without understanding of the steps. To illustrate the differences I like to use visuals.
In the imperative model we assemble our lunch by assembling the various components together. In this model we can have many specialists involved to assure we have the best product in our lunch. We have a cheese specialist ensuring awesome cheese. We have a meat specialist choosing prime cuts. When someone comes to the bar to assemble their lunch chaos becomes reality. I may not fully understand the flavors provided by the specialist and choose to assemble a mess. If I include every specialist in the assembly I am likely to get a great sandwich but this process cannot scale. The imperative model thus is focused on the individual steps to produce an outcome.
In the declarative model the end state is defined and the system is trusted to produce the outcome. The meal above represents my request for a good dinner. I was not concerned with platting or cooking I just wanted a meal.
Why should you care about my lunch/dinner?
Allow me to illustrate the value of declarative models in detail. Let us assume you have two switches and two routers in your network:
In imperative models we are hyper focused on the steps to make this networking construct redundant. It may involve linking switches and using BGP or OSPF to ensure optimal paths. This added human complexity provides a job for many people. Now lets examine the functional differences between two options:
Functionally assuming the user can detect upstream failures there is no difference. You avoid a single point of failure and communication continues. In a declarative model all we would need to define is IP method to get from point user to router and no single point of failure. Kubernetes implements a declarative model that creates initial state and ensures that desired state continues until changed which yields the real power of declarative models. For example lets look at this application definition:
apiVersion: extensions/v1 kind: Deployment metadata: name: site spec: replicas: 2 template: metadata: labels: app: web spec: containers: - name: front-end image: nginx ports: - containerPort: 80 - name: reader image: nginx ports: - containerPort: 88
This declarative yaml creates four pods in a deployment (2 front-end, 2 reader). If you manually remove one of these pods a new pod is redeployed to ensure the declarative state exists. So when we implement declarative models we can ensure desired state long past imperative models.