Modern organizations often operate across multiple data platforms and technologies. To support flexible, scalable data architectures, iprosis works with market leading platforms that enable advanced analytics, AI, and data-driven exploration.
Databricks enables organizations to build, process, and analyze large volumes of data at scale, supporting advanced analytics and machine learning workloads.
Built on the Lakehouse architecture, Databricks combines data engineering, exploratory analytics, machine learning, and real-time data pipelines in a single environment. It is commonly used for large-scale data processing and AI development.
Databricks can also integrate SAP BDC data into open and cloud-native data architecture.
Snowflake enables scalable analytics and secure data sharing across cloud environments, supporting high-performance analytical workloads with minimal operational overhead.
As a cloud-native data platform, Snowflake separates compute and storage to provide elasticity, concurrency, and cost efficiency. It is widely used for enterprise analytics, governed data sharing, and multi-cloud data architectures.
Snowflake can also integrate SAP BDC data into open and cloud-native data architecture.