What is the difference between single-tenant and E2 architecture?

[Taha]

These are essentially two different types of deployment model at Databricks. Single-tenant is the legacy deployment architecture that is being phased out with E2 being a name for the replacement.

There were several limitations and constraints that E2 helps solve for and makes both governance and customization easier and broader. With E2 workspaces, you can create and manage multiple workspaces associated with a single Databricks account (through an API), deploy into custom VPCs, and more. There are even improvements with update rollouts and maintenance windows that will be coming in the future.

To get more details on this or to see how this can fit in with your governance strategy, I'd recommend reaching out to a Databricks representative since there are a lot more improvements than the few I've mentioned here.

[amr]

Good explanation by @taha syed​, Just adding that there is actually a third deployment model, which is PVC (Private Virtual CLoud), that is to run Databricks entirely inside the customer account, this options is very costly and will require additional checks by Databricks to support, however, it is useful to big customers who want everything inside their account.

[NubeEra]

Databricks provides 4 main deployment models they are:

1. Public Cloud Deployment Model: Databricks can be deployed on public cloud platforms such as AWS, Azure, and Google Cloud Platform. This is the most common deployment model for Databricks and provides a scalable and flexible environment for data processing.
2. Private Virtual Cloud Deployment Model: Databricks can also be deployed in a private virtual cloud, such as a VMware-based virtualized environment. This deployment model provides greater control and security over the Databricks environment.
3. Enterprise Edition (E2) Deployment Model: The E2 deployment model provides a highly scalable and multi-tenant environment for Databricks. It includes advanced features such as Delta Lake, automated machine learning, and advanced security and governance features.
4. Single Tenant Deployment Model: The single-tenant deployment model allows organizations to deploy Databricks in a dedicated environment, providing greater control and isolation over the Databricks environment. This deployment model is well-suited for organizations with strict security or compliance requirements.

E2 Deployment Model vs Single Tenant Deployment Model

The benefits and differences between(E2 and Single Tenant) the two are:

1. Architecture: The E2 model is built on a shared architecture, where multiple customers share the same underlying compute and storage infrastructure. The Single Tenant Deployment model provides dedicated infrastructure for each customer.
2. Scalability: The E2 model is highly scalable, allowing customers to quickly provision and deprovision compute and storage resources as needed. The Single Tenant Deployment model provides dedicated infrastructure, which may limit scalability in some cases.
3. Cost: The E2 model is typically more cost-effective than the Single Tenant Deployment model, as customers share infrastructure costs. The Single Tenant Deployment model provides dedicated infrastructure, which may result in higher costs.
4. Security: The E2 model provides multi-tenancy security controls to protect customer data, such as encryption and access controls. The Single Tenant Deployment model provides dedicated infrastructure, which may provide additional security benefits.
5. Customization: The Single Tenant Deployment model allows for more customization and control over the underlying infrastructure, as customers have dedicated resources. The E2 model provides a standardized architecture and may have limitations on customization.
6. Support: The E2 model provides 24/7 support and has a large community of users and developers. The Single Tenant Deployment model may have more limited support options.

Short Summary:

Enterprise Edition (E2) Deployment Model:

• Scalability: The E2 model provides a highly scalable architecture that can handle large-scale data processing workloads with ease.
• Multi-tenancy: E2 allows multiple users to share resources, which can lead to significant cost savings and more efficient use of resources.
• Integrated data lake: E2 includes an integrated data lake (Delta Lake), which provides advanced data management features such as ACID transactions, schema enforcement, and data versioning.
• Automated machine learning: E2 includes automated machine learning features, which can help data scientists quickly develop and deploy machine learning models.

Single Tenant Deployment Model:

• Customization: With a single-tenant deployment model, organizations can customize the Databricks environment to meet their specific needs, such as adding custom libraries, configuring network settings, and installing custom software.
• Isolation: Single-tenant deployments offer greater isolation and control over the environment, which can be important for organizations with strict security or compliance requirements.
• Predictable costs: With a single-tenant deployment model, organizations can predict their costs more accurately, since they are not sharing resources with other users.

Overall, the choice between the E2 model and the Single Tenant Deployment model depends on the specific needs and requirements of the organization. The E2 model is highly scalable, cost-effective, and provides multi-tenancy security controls. The Single Tenant Deployment model provides dedicated infrastructure and may offer more customization and control, but may also have higher costs and more limited scalability.