The Iguazio Data Science Platform (“the platform”) provides enterprises with the flexibility to run applications on-premises (“on-prem”) or in an edge or hybrid cloud architecture. The platform was built from the ground up to maximize CPU utilization and leverage the benefits of non-volatile memory, 100 GbE remote direct memory access (RDMA), flash memory, and dense storage. This design enables the platform to achieve extreme performance while maintaining data consistency, at the lowest cost.
The platform is available in two configurations, which differ in a variety of aspects, including the performance capacity, footprint, storage size, and scale capabilities:
- Development Kit
- A single data-node and single application-node cluster implementation. This configuration is designed mainly for evaluation trials and doesn’t include high availability (HA) or performance testing.
- Operational Cluster
- A scalable cluster implementation that is composed of multiple data and application nodes. This configuration was designed to achieve superior performance that enables real-time execution of analytics, machine-learning (ML), and artificial-intelligence (AI) applications in a production pipeline. The minimum requirement for HA support is three data nodes and three application nodes.
The platform supports the following alternative deployment methods:
- Deployment on an Amazon Web Services (AWS) or Microsoft Azure cloud — either as part of your virtual private cloud (VPC) or virtual network (VNet) or as a software as a service (SaaS) in Iguazio’s cloud account. See the Cloud Hardware Specifications.
- On-premises deployment. The data nodes are deployed on virtual machines (VMs), and the application nodes can optionally be deployed either on VMs or on physical machines (bare-metal). See the On-Premises Hardware Specifications.
- All capacity calculations in the hardware specifications are performed using the base-10 (decimal) number system. For example, 1 TB = 1,000,000,000,000 bytes.