Question: I need a solution that can support a variety of workloads, including AI/ML and data lakes, do you know of any?

If you're looking for a solution that spans a range of workloads, including AI/ML and data lakes, Databricks is a good choice. It incorporates generative AI to integrate data, analytics and governance so you can build and run AI applications directly against your data. With its lakehouse architecture, it provides open, scalable and unified data management, making it a good choice for users who need a single data intelligence platform.

Another powerful option is Teradata, a cloud analytics and data platform that's designed to integrate and harmonize data across an enterprise. It supports multiple workloads, including AI/ML, data lakes, data warehouses and data engineering. With its ClearScape Analytics feature, Teradata provides a single view of your data and faster insights, and it can be deployed in public cloud, hybrid cloud and on-premises environments.

If you need a hybrid data platform that spans cloud and on-premises environments, Cloudera is also worth a look. It securely ingests, processes and analyzes large amounts of data from many sources into a single trusted system, enabling real-time insights and AI model training. Built on Apache Iceberg, the platform ensures data reliability and flexibility so you can manage data lakehouses across multiple clouds and overcome data silos.

Informatica also offers a cloud-based, AI-powered data management solution that integrates and manages data across multi-cloud and hybrid environments. It uses its CLAIRE AI engine to automate data integration tasks and offers features like data catalog, data integration and observability, making it a good choice for businesses that want to modernize their data management and make their data AI-ready.